The present disclosure relates to systems and techniques for data integration, analysis, and visualization. More specifically, the present disclosure relates to visualization of law enforcement agency data.
Law enforcement agencies (e.g., a police department of a city) can monitor emergency calls in a designated area. Systems and methods for allowing such agencies to better (e.g., more quickly, more accurately, etc.) interact with such data are desired.
The systems, methods, and devices described herein each have several aspects, no single one of which is solely responsible for its desirable attributes. Without limiting the scope of this disclosure, several non-limiting features will now be discussed briefly.
In one embodiment, a computer system configured to provide a customizable user interface relating to visualization of data associated with a law enforcement agency comprises: one or more hardware computer processors configured to execute code in order to cause the system to: generate a user interface configured to concurrently display a plurality of panels each including a visual representation based on emergency call data of a law enforcement agency, the emergency call data comprising data associated with a plurality of emergency calls, wherein the plurality of panels comprises at least: a first panel displaying a map of a geographical region associated with the law enforcement agency, the map of the geographical region comprising a plurality of selectable precinct indicators representing a corresponding plurality of precincts for which the law enforcement agency has at least some law enforcement responsibilities, the first panel configured to: in response to receiving a selection of a particular precinct indicator corresponding to a particular precinct, update the first panel to display one or more emergency call indicators representing a corresponding one or more emergency calls within the particular precinct; and in response to receiving a selection of a particular emergency call indicator corresponding to a particular emergency call, update the first panel to display information relating to the particular emergency call.
In another embodiment, a method of providing a customizable user interface relating to visualization of data associated with a law enforcement agency comprises: generating, using one or more hardware computer processors, a user interface configured to concurrently display a plurality of panels each including a visual representation based on emergency call data of a law enforcement agency, the emergency call data comprising data associated with a plurality of emergency calls; displaying in the user interface at least a first panel of the plurality of panels, the first panel displaying a map of a geographical region associated with the law enforcement agency, the map of the geographical region comprising a plurality of selectable precinct indicators representing a corresponding plurality of precincts for which the law enforcement agency has at least some law enforcement responsibilities; in response to receiving a selection of a particular precinct indicator corresponding to a particular precinct, updating the first panel to display one or more emergency call indicators representing a corresponding one or more emergency calls within the particular precinct; and in response to receiving a selection of a particular emergency call indicator corresponding to a particular emergency call, updating the first panel to display information relating to the particular emergency call.
In yet another embodiment, a non-transitory computer readable medium comprises instructions for providing a customizable user interface relating to visualization of data associated with a law enforcement agency that cause a computer processor to: generate a user interface configured to concurrently display a plurality of panels each including a visual representation based on emergency call data of a law enforcement agency, the emergency call data comprising data associated with a plurality of emergency calls; display in the user interface at least a first panel of the plurality of panels, the first panel displaying a map of a geographical region associated with the law enforcement agency, the map of the geographical region comprising a plurality of selectable precinct indicators representing a corresponding plurality of precincts for which the law enforcement agency has at least some law enforcement responsibilities; in response to receiving a selection of a particular precinct indicator corresponding to a particular precinct, update the first panel to display one or more emergency call indicators representing a corresponding one or more emergency calls within the particular precinct; and in response to receiving a selection of a particular emergency call indicator corresponding to a particular emergency call, update the first panel to display information relating to the particular emergency call.
Overview
Techniques in this disclosure may provide a user interface that concurrently displays multiple panels which provide visualization of emergency call data of a law enforcement agency, such as data that is specifically pertinent to a particular agency director/supervisor. For example, the panels on an “executive dashboard,” may be customized to include the most relevant/useful data for a particular user, department, or agency, for example. In one embodiment, the panels provide summary data that is useful for a director, supervisor, or other “executive,” while still allowing the executive to drill down into the data in order to view detailed information about any summarized data. For example, top officials or decision makers of a law enforcement agency, such as police chiefs or sheriffs, may not be interested in the details of each call, but would want to know which sections or divisions in the geographical area have a high level of unassigned calls.
The user interface can provide a high-level overview of emergency calls in a geographical area that is overseen by the law enforcement agency. Examples of law enforcement agencies include police departments (e.g., NYPD, LAPD, etc.), sheriff's departments, etc. Each panel in the user interface can provide a visualization (e.g., a chart, graph, diagram, list, map, drawing, etc.) indicating aspects related to emergency calls and/or statistics relating to the calls. For example, the user interface can include a panel that displays the number of emergency calls by precinct or section on a map of the geographical area.
A user (e.g., system administrator, analyst, etc.) can customize which panels to include in the user interface and/or customize setting for each panel. For instance, the user can specify which panels should be included in the user interface, dimensions and/or size of a panel, the order in which the panels should be displayed, etc. Then, the user interface can determine the optimal layout and display the panels according to the user specified requirements. In one embodiment, a first user, such as a system administrator, customizes the user interface for use by one or more other users, such as analysts. Alternatively, the user that views and interacts with the user interface may customize the user interface.
The user may apply various types of filters to the data displayed in the user interface, and the panels can update the visualizations according to the filters. For example, the user may wish to view emergency calls in a specific time frame and apply a filter for that time frame, and the visualizations in all or some of the panels can be automatically updated to show the results of applying the filter. The user interface can also provide the ability to show data at various levels of detail within the same user interface. For instance, the user can click on an emergency call in the precinct or section, and the details of the call can be displayed in the same panel. In this manner, the techniques in the disclosure can provide a convenient, digestible overview of tactical and/or strategic data in a single user interface.
In one embodiment, the executive dashboard allows a user to easily identify trends (geographic, temporal, etc.) based on Computer Aided Dispatch (CAD) Job data. Maps allow the user to visualize CAD Jobs geographically, with the option to view the map with a street view or based on precinct zones. Various charts also display time-based trends, allowing users to compare current conditions with conditions from last week (or another time in the past). Filters allow the user to drill down further based on various criteria, including radio code, precinct, and status. These features, as well as others that may be implemented in various embodiments, are discuss further below.
Example Executive Dashboard
As explained above, the panels 110 in the user interface 100 can be customized, and the settings for a panel 110 can also be customized. The user can choose the types of panels 110 that are included in the user interface 100. Some examples of types of panels 110 include, where panels are referenced based on a type of visualization included with the panels: map, table, bar chart, line graph, flow diagram, word cloud diagram, etc. Visualizations may also be referred to as a “visual representations.” These types of panels 110 are further explained with respect to
The user can also specify the dimensions or size for a particular panel 110 and/or multiple or all panels 110. In one embodiment, the size of a panel 110 is defined by number of rows and columns, and the layout engine renders the panels 110 in the user interface 100 based on the size of each panel 110. Specifying in terms of rows and columns may make the process simpler since the user does not have to use pixels. For instance, the rows and columns may be defined by a unit that is associated with a group of pixels. The sizes of panels 110 can be the same or different from each other. In some embodiments, the user may define the number of columns in the user interface 100, and the panels 110 are arranged in columns. The customization setting for the panels 110 may be specified for an individual, a group of individuals, the entire organization, etc.
The user interface 100 may also include one or more filters 150 to apply to the data displayed in the user interface 100. Types of filters can include: keyword filters, date filters, area filters (e.g., precinct or other geographic filters), call information filters (e.g., radio code, caller information, etc), or filters based on any other attribute associated with the emergency call data. Such filters may be configured using any available user interface controls, such as radio buttons, drop-down lists, text entry fields, etc. The example in
The time filter 150b can accept a time frame or time period from the user. The time frame may be a range, a specific time, or a specific date. The time filter 150b can be selected using a date picker, a drop down menu that provides a list of time frames as options, or other user interface controls. The precinct filter 150c and the patrol borough filter 150d can filter the data by precinct and by patrol borough, respectively. They may be drop down menus (or other user interface controls) that provide a list of precincts and a list of patrol boroughs. In one example, a patrol borough consists of one or more precincts (e.g., in New York City). The list of precincts provided by the precinct filter 150c can vary based on the borough selected in the patrol borough filter 150d. A “precinct” may refer to a geographical section or division within a geographical area that is served by or is under the jurisdiction of a particular law enforcement agency. Different terms may be used by various law enforcement agencies to refer to such geographical section or division within the geographical area (e.g., “area”, “division,” etc.).
The type and/or content of information displayed in the panels 110 and/or the user interface 100 may vary depending on the requirements of a law enforcement agency. For example, one law enforcement agency could be interested in viewing emergency call data; this law enforcement agency may want to view data for various precincts and quickly determine which precincts have a backlog in terms of resource assignment. The user interface 100 and the panels 110 can show which precincts have a high number of jobs that are not assigned to a resource. On the other hand, another law enforcement agency might be more interested in viewing arrest data. Examples of user interface and panels displaying arrest data are discussed in detail in connection with
The user interface 100 may be generated by systems described with respect to
A panel 110 can include any type of visualization. For example, the panels 110 in the user interface 100 may include any of the visualizations illustrated in
Example Drill-Down of Emergency Call Data
In
In
If any filters are applied in the user interface, as in
Other Example Panels
In the example of
Example Executive Dashboard
In the example of
Other types of visualizations can include a line graph, object summary, pie chart, time wheel, time series chart, etc. A time wheel may refer to a circular representation of a unit of time (e.g., an hour, a day, a week, a month), which may be subdivided into smaller units of time. The panels 710 can be similar to the panels 110 in the user interface 100. A panel 710 can include any type of visualization. For example, the panels 710 in the user interface 700 may include any of the visualizations illustrated in
Similar to
The user interface 700 can be configured so that visualizations in all of the panels 710 may be automatically updated (e.g., in realtime). In one embodiment, the visualizations are updated in response to changes to the filter criteria. In another embodiment, only a portion of the panels 710 are updated in response to filter changes, such as a predefined set of panels 710 and/or a user selected group of panels 710. In this way, the user may be able to view unfiltered data in one or more panels 710, while adjusting filters that are automatically applied to other panels 710. In another embodiment, different sets of filters may be applied to different sets of one or more panels 710.
The user interface 700 or the user interface 100 may be implemented as a layer on top of systems using object centric data models as described with respect to
A platform may be provided for building overview layers for object-centric systems. For example, such platform can be provided by the systems described in
The platform may also provide general scripts that can be used to create customized user interfaces so that the user does not have to write code. Such scripts can include SQL or proprietary scripts, for example. In some embodiments, the platform provides a configuration plugin template, and the user can use a command line to start implementing the overview user interface or the executive dashboard. The template may specify the configurations and/or settings for generating the customized user interface 700, 100. The platform can allow various aspects of the user interface 700, 100 to be configured, such as by using a visualization framework, configuration framework, and/or layout framework. In one embodiment, the visualization framework allows users to implement their own visualizations that can be used in the dashboard. The configuration framework may allow users to implement their own data source and transform the data to be displayed in a visualization. The layout framework may take the requested size of a visualization (e.g., 2 rows high and 2 columns wide) and fit it into the dashboard's layout.
One of the features of the user interface 700, 100 is that customization of panels 710, 110 in the user interface 700, 100 can be simple and easy for the users. The panels 710, 110 may be easily rearranged, and the dimensions of the panels 710, 110 can be specified in a simple manner (e.g., by number of rows and columns). In one embodiment, a panel 710, 110 can be dragged to a location within the user interface 700, 100 to arrange its position. In another embodiment, the user can add or select panels 710, 110 of the user's choice to create a customized user interface 700, 100 (e.g., in real-time). The user interface 700, 100 may be a web interface.
Other aspects of the user interface 700, 100 may also be configured and customized. Such aspects can include pages, page layout, security settings, visualizations, etc. In some embodiments, the user interface 700, 100 are organized as multiple pages, and one page of the user interface 700, 100 may be displayed at one time. The different pages may be grouped by categories. Similarly, the panels 710, 110 can be grouped by categories. Access or security settings may be specified for a group of pages or panels 710, 110, and only those with the access privileges may be able to view a certain page or panel 710, 110. For example, if a user does not have access rights to a particular panel 710, 110, the user interface 700, 100 would not display the panel 710, 110 for that user. The features of a visualization could also be customized. For example, the user can specify the maximum length of a bar in a bar chart within the panel 710, 110 or the colors used for the bars.
In certain embodiments, the user interface 700, 100 detects or is otherwise aware of the user interface mode in which it is displayed and adjusts the way the user interface 700, 100 is presented on a display device. For example, the user interface 700, 100 may be displayed in full screen mode. The user interface mode (“UI mode”) can be designated by a specific application. For large screens (e.g., 10-foot display), the user interface 700, 100 could be displayed for showcasing purposes, rather than (or in addition to) performing daily operations. In such case, the user interface 700, 100 can be adjusted to be more fitting for large screens. The UI mode for displaying on large screens may be referred to as “large screen mode” or “10-foot mode.” In large screen mode, the user interface 700, 100 may not concurrently display the panels 710, 110, but instead rotate one or more panels 710, 110 at an interval. Also, filters 750, 150 may not be displayed, and fewer details may be shown in the user interface 700, 100 and/or the panels 710, 110. Text and/or graphical elements can be larger so they can be seen from a distance. Each panel 710, 110 may also know about the UI mode and adjust itself to be more appropriately displayed in a selected UI mode.
Figures have been explained with respect to law enforcement agencies, but the user interfaces described in this disclosure may be used by other types of organizations. Some examples include fire departments, offices of mayors, etc. Fire departments may use the overview user interface to track service calls. A mayor's office may use the overview user interface to manage building jobs and building complaints. For example, by viewing the building jobs and building complaints in the same panel or user interface, the mayor's office can note any correlations between the jobs and the complaints at a glance. As explained above, the techniques of this disclosure may provide a user interface 700, 100 that can be easily configured and customized and that can display a customizable overview of high-level data. The overview data can assist decision makers in obtaining relevant data at a glance and making informed decisions.
The map 810 is configured to allow the user to drill down from a larger area to a smaller area. In one example, the map 810 starts with showing a country (e.g., the U.S.). The user clicks (or scrolls, presses a certain key, provides an audible command, or any other predefined input) on a state within the country, and the map 810 zooms in to show the state. The user clicks on a county in the state, and the map 810 zooms in to display the county. The user then can click on a city in the county, and the map 810 zooms in to show the details for that city, and so forth. In this way, the same panel or user interface can display information of varying levels of depth.
Filters can narrow or drill down the information displayed in the user interface 700,100 and/or the panels 710, 110. Filters can be temporal filters or object filters. Information displayed in the panels 710, 110 can be represented by objects, and object filters may filter data based on various properties of objects. Different types of filters may include: a keyword filter, a date filter, a time filter, a multiple value filter, etc. A keyword filter can accept one or more keywords for filtering the data. A keyword filter may support full-text searching. For example, full texts of objects can be searched. A date filter, a time filter, or a date picker may allow the user to select a specific time, date, range of time, range of date, etc. A multiple value or multi-value filter may accept more than one value for filtering the data. Users may also create their own filters (e.g., as plug-in filters). Various types of filters may be used in combination. For example, one filter is both a keyword filter and a multi-value filter; the user can enter one or more keywords in the keyword filter.
When filters are applied in the user interface 700, 100 or a panel 710, 110 in the user interface 700, 100, the user interface 700,100 or the panel 710, 110 can show an indication that the data has been filtered. For example, the user interface 700, 100 can include a button for undoing the filtering or returning to the previous unfiltered data, or the user interface 700, 100 can have a reset button to return to the initial view without any filtering. Applying a filter in one panel 710, 110 may filter the data in some or all of the other panels 710, 110. Generally, the filter will apply to the panels 710, 110 included in the user interface 700, 100. However, in some cases, application of the filter to a particular panel 710, 110 may make it more difficult for the user to navigate. For example, in
Example Method
At block 902, the process 900 generates a user interface 100 configured to concurrently display a plurality of panels 110 each including a visual representation based on emergency call data of a law enforcement agency. In this embodiment, the emergency call data includes data associated with a plurality of emergency calls. Types of visual representation or visualizations included in a panel 110 may include: a map, a bar chart, a table, a line graph, a time series chart, an object summary, a flow diagram, a word diagram, a pie chart, a time wheel, etc. The details relating to each type of visual representation are explained with respect to
At block 904, a map panel of a geographical region associated with the law enforcement agency is included in the user interface (such as the first panel 110a discussed above). The map of the geographical region may include a plurality of selectable precinct indicators representing a corresponding plurality of precincts for which the law enforcement agency has at least some law enforcement responsibilities. The plurality of precinct indicators may each show the number of emergency calls in a particular precinct. The precinct indicators may have different colors to convey information at a glance. For example, indicators for precincts with high number of emergency calls may be shown in orange; indicators for precincts with low number of emergency calls may be shown in green.
At block 906, in response to receiving a selection (e.g., from an executive viewing the executive dashboard) of a particular precinct indicator corresponding to a particular precinct, the map panel is updated to display one or more emergency call indicators representing a corresponding one or more emergency calls within the selected precinct. Emergency calls may be represented as objects and have properties associated with them, such as job ID, time and date, location, radio code, assigned resource, comments, etc. The one or more emergency call indicators can have different colors and/or shapes to convey information quickly. For example, different colors correspond to different types of jobs or radio codes, and different shapes indicate how recent the emergency calls are.
At block 908, in response to receiving a selection of a particular emergency call indicator corresponding to a particular emergency call, the map panel is updated to display information relating to the particular emergency call. Information about the emergency call may be displayed on the map itself or in a separate pop-up window. In one example, brief information is shown on the map itself, next to the emergency call indicator, and detailed information is displayed in the separate pop-up window. The details may include job number, time and date, location, comments, etc.
In certain embodiments, a second panel displaying a statistic relating to at least some of the emergency call data is included in the user interface. In one embodiment, the statistic in the second panel is associated with the one or more emergency calls within the particular precinct. In another embodiment, the statistic in the second panel is associated with emergency calls in all of the plurality of precincts in the geographical region.
In some embodiments, a filter may be applied to the map panel. Applying the filter may update the map panel to display the one or more emergency call indicators that meet criteria indicated by the filter. Types of filters can include: a keyword filter, a date filter, a time filter, a multiple value filter, etc. The filter applied in the map panel can also be applied in the second panel and/or another panel of the plurality of panels.
The type of information displayed in the panels may include: high priority emergency calls, historical trend of emergency calls, top radio codes, top radio subcodes, etc. For example, the plurality of panels other than the map panel can display any of the different types of information listed above.
In order to facilitate an understanding of the systems and methods discussed herein, a number of terms are defined below. The terms defined below, as well as other terms used herein, should be construed to include the provided definitions, the ordinary and customary meaning of the terms, and/or any other implied meaning for the respective terms. Thus, the definitions below do not limit the meaning of these terms, but only provide exemplary definitions.
Ontology: Stored information that provides a data model for storage of data in one or more databases. For example, the stored data may comprise definitions for object types and property types for data in a database, and how objects and properties may be related.
Database: A broad term for any data structure for storing and/or organizing data, including, but not limited to, relational databases (Oracle database, mySQL database, etc.), spreadsheets, XML files, and text file, among others.
Data Object or Object: A data container for information representing specific things in the world that have a number of definable properties. For example, a data object can represent an entity such as a person, a place, an organization, a market instrument, or other noun. A data object can represent an event that happens at a point in time or for a duration. A data object can represent a document or other unstructured data source such as an e-mail message, a news report, or a written paper or article. Each data object may be associated with a unique identifier that uniquely identifies the data object. The object's attributes (e.g. metadata about the object) may be represented in one or more properties.
Object Type: Type of a data object (e.g., Person, Event, or Document). Object types may be defined by an ontology and may be modified or updated to include additional object types. An object definition (e.g., in an ontology) may include how the object is related to other objects, such as being a sub-object type of another object type (e.g. an agent may be a sub-object type of a person object type), and the properties the object type may have.
Properties: Attributes of a data object that represent individual data items. At a minimum, each property of a data object has a property type and a value or values.
Property Type: The type of data a property is, such as a string, an integer, or a double. Property types may include complex property types, such as a series data values associated with timed ticks (e.g. a time series), etc.
Property Value: The value associated with a property, which is of the type indicated in the property type associated with the property. A property may have multiple values.
Link: A connection between two data objects, based on, for example, a relationship, an event, and/or matching properties. Links may be directional, such as one representing a payment from person A to B, or bidirectional.
Link Set: Set of multiple links that are shared between two or more data objects.
Object Centric Data Model
To provide a framework for the following discussion of specific systems and methods described herein, an example database system 1210 using an ontology 1205 will now be described. This description is provided for the purpose of providing an example and is not intended to limit the techniques to the example data model, the example database system, or the example database system's use of an ontology to represent information.
In one embodiment, a body of data is conceptually structured according to an object-centric data model represented by ontology 1205. The conceptual data model is independent of any particular database used for durably storing one or more database(s) 1209 based on the ontology 1205. For example, each object of the conceptual data model may correspond to one or more rows in a relational database or an entry in Lightweight Directory Access Protocol (LDAP) database, or any combination of one or more databases.
Different types of data objects may have different property types. For example, a “Person” data object might have an “Eye Color” property type and an “Event” data object might have a “Date” property type. Each property 203 as represented by data in the database system 1210 may have a property type defined by the ontology 1205 used by the database 1205.
Objects may be instantiated in the database 1209 in accordance with the corresponding object definition for the particular object in the ontology 1205. For example, a specific monetary payment (e.g., an object of type “event”) of US$30.00 (e.g., a property of type “currency”) taking place on Mar. 27, 2009 (e.g., a property of type “date”) may be stored in the database 1209 as an event object with associated currency and date properties as defined within the ontology 1205.
The data objects defined in the ontology 1205 may support property multiplicity. In particular, a data object 1201 may be allowed to have more than one property 203 of the same property type. For example, a “Person” data object might have multiple “Address” properties or multiple “Name” properties.
Each link 1202 represents a connection between two data objects 1201. In one embodiment, the connection is either through a relationship, an event, or through matching properties. A relationship connection may be asymmetrical or symmetrical. For example, “Person” data object A may be connected to “Person” data object B by a “Child Of” relationship (where “Person” data object B has an asymmetric “Parent Of” relationship to “Person” data object A), a “Kin Of” symmetric relationship to “Person” data object C, and an asymmetric “Member Of” relationship to “Organization” data object X. The type of relationship between two data objects may vary depending on the types of the data objects. For example, “Person” data object A may have an “Appears In” relationship with “Document” data object Y or have a “Participate In” relationship with “Event” data object E. As an example of an event connection, two “Person” data objects may be connected by an “Airline Flight” data object representing a particular airline flight if they traveled together on that flight, or by a “Meeting” data object representing a particular meeting if they both attended that meeting. In one embodiment, when two data objects are connected by an event, they are also connected by relationships, in which each data object has a specific relationship to the event, such as, for example, an “Appears In” relationship.
As an example of a matching properties connection, two “Person” data objects representing a brother and a sister, may both have an “Address” property that indicates where they live. If the brother and the sister live in the same home, then their “Address” properties likely contain similar, if not identical property values. In one embodiment, a link between two data objects may be established based on similar or matching properties (e.g., property types and/or property values) of the data objects. These are just some examples of the types of connections that may be represented by a link and other types of connections may be represented; embodiments are not limited to any particular types of connections between data objects. For example, a document might contain references to two different objects. For example, a document may contain a reference to a payment (one object), and a person (a second object). A link between these two objects may represent a connection between these two entities through their co-occurrence within the same document.
Each data object 1201 can have multiple links with another data object 1201 to form a link set 1204. For example, two “Person” data objects representing a husband and a wife could be linked through a “Spouse Of” relationship, a matching “Address” property, and one or more matching “Event” properties (e.g., a wedding). Each link 1202 as represented by data in a database may have a link type defined by the database ontology used by the database.
Implementation Mechanisms
According to one embodiment, the techniques described herein are implemented by one or more special-purpose computing devices. The special-purpose computing devices may be hard-wired to perform the techniques, or may include circuitry or digital electronic devices such as one or more application-specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs) that are persistently programmed to perform the techniques, or may include one or more hardware processors programmed to perform the techniques pursuant to program instructions in firmware, memory, other storage, or a combination. Such special-purpose computing devices may also combine custom hard-wired logic, ASICs, or FPGAs with custom programming to accomplish the techniques. The special-purpose computing devices may be desktop computer systems, server computer systems, portable computer systems, handheld devices, networking devices or any other device or combination of devices that incorporate hard-wired and/or program logic to implement the techniques.
Computing device(s) are generally controlled and coordinated by operating system software, such as iOS, Android, Chrome OS, Windows XP, Windows Vista, Windows 7, Windows 8, Windows Server, Windows CE, Unix, Linux, SunOS, Solaris, iOS, Blackberry OS, VxWorks, or other compatible operating systems. In other embodiments, the computing device may be controlled by a proprietary operating system. Conventional operating systems control and schedule computer processes for execution, perform memory management, provide file system, networking, I/O services, and provide a user interface functionality, such as a graphical user interface (“GUI”), among other things.
For example,
Computer system 1800 includes a bus 1802 or other communication mechanism for communicating information, and a hardware processor, or multiple processors, 1804 coupled with bus 1802 for processing information. Hardware processor(s) 1804 may be, for example, one or more general purpose microprocessors.
Computer system 1800 also includes a main memory 1806, such as a random access memory (RAM), cache and/or other dynamic storage devices, coupled to bus 1802 for storing information and instructions to be executed by processor 1804. Main memory 1806 also may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor 1804. Such instructions, when stored in storage media accessible to processor 1804, render computer system 1800 into a special-purpose machine that is customized to perform the operations specified in the instructions.
Computer system 1800 further includes a read only memory (ROM) 808 or other static storage device coupled to bus 1802 for storing static information and instructions for processor 1804. A storage device 1810, such as a magnetic disk, optical disk, or USB thumb drive (Flash drive), etc., is provided and coupled to bus 1802 for storing information and instructions.
Computer system 1800 may be coupled via bus 1802 to a display 1812, such as a cathode ray tube (CRT) or LCD display (or touch screen), for displaying information to a computer user. An input device 1814, including alphanumeric and other keys, is coupled to bus 1802 for communicating information and command selections to processor 1804. Another type of user input device is cursor control 1816, such as a mouse, a trackball, or cursor direction keys for communicating direction information and command selections to processor 1804 and for controlling cursor movement on display 1812. This input device typically has two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allows the device to specify positions in a plane. In some embodiments, the same direction information and command selections as cursor control may be implemented via receiving touches on a touch screen without a cursor.
Computing system 1800 may include a user interface module to implement a GUI that may be stored in a mass storage device as executable software codes that are executed by the computing device(s). This and other modules may include, by way of example, components, such as software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables.
In general, the word “module,” as used herein, refers to logic embodied in hardware or firmware, or to a collection of software instructions, possibly having entry and exit points, written in a programming language, such as, for example, Java, Lua, C or C++. A software module may be compiled and linked into an executable program, installed in a dynamic link library, or may be written in an interpreted programming language such as, for example, BASIC, Perl, or Python. It will be appreciated that software modules may be callable from other modules or from themselves, and/or may be invoked in response to detected events or interrupts. Software modules configured for execution on computing devices may be provided on a computer readable medium, such as a compact disc, digital video disc, flash drive, magnetic disc, or any other tangible medium, or as a digital download (and may be originally stored in a compressed or installable format that requires installation, decompression or decryption prior to execution). Such software code may be stored, partially or fully, on a memory device of the executing computing device, for execution by the computing device. Software instructions may be embedded in firmware, such as an EPROM. It will be further appreciated that hardware modules may be comprised of connected logic units, such as gates and flip-flops, and/or may be comprised of programmable units, such as programmable gate arrays or processors. The modules or computing device functionality described herein are preferably implemented as software modules, but may be represented in hardware or firmware. Generally, the modules described herein refer to logical modules that may be combined with other modules or divided into sub-modules despite their physical organization or storage
Computer system 1800 may implement the techniques described herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware and/or program logic which in combination with the computer system causes or programs computer system 1800 to be a special-purpose machine. According to one embodiment, the techniques herein are performed by computer system 1800 in response to processor(s) 1804 executing one or more sequences of one or more instructions contained in main memory 1806. Such instructions may be read into main memory 1806 from another storage medium, such as storage device 1810. Execution of the sequences of instructions contained in main memory 1806 causes processor(s) 1804 to perform the process steps described herein. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions.
The term “non-transitory media,” and similar terms, as used herein refers to any media that store data and/or instructions that cause a machine to operate in a specific fashion. Such non-transitory media may comprise non-volatile media and/or volatile media. Non-volatile media includes, for example, optical or magnetic disks, such as storage device 1810. Volatile media includes dynamic memory, such as main memory 1806. Common forms of non-transitory media include, for example, a floppy disk, a flexible disk, hard disk, solid state drive, magnetic tape, or any other magnetic data storage medium, a CD-ROM, any other optical data storage medium, any physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, NVRAM, any other memory chip or cartridge, and networked versions of the same.
Non-transitory media is distinct from but may be used in conjunction with transmission media. Transmission media participates in transferring information between nontransitory media. For example, transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise bus 1802. Transmission media can also take the form of acoustic or light waves, such as those generated during radio-wave and infra-red data communications.
Various forms of media may be involved in carrying one or more sequences of one or more instructions to processor 1804 for execution. For example, the instructions may initially be carried on a magnetic disk or solid state drive of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to computer system 1800 can receive the data on the telephone line and use an infra-red transmitter to convert the data to an infra-red signal. An infra-red detector can receive the data carried in the infra-red signal and appropriate circuitry can place the data on bus 1802. Bus 1802 carries the data to main memory 1806, from which processor 1804 retrieves and executes the instructions. The instructions received by main memory 1806 may retrieves and executes the instructions. The instructions received by main memory 1806 may optionally be stored on storage device 1810 either before or after execution by processor 1804.
Computer system 1800 also includes a communication interface 1818 coupled to bus 1802. Communication interface 1818 provides a two-way data communication coupling to a network link 1820 that is connected to a local network 1822. For example, communication interface 1818 may be an integrated services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, communication interface 1818 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN (or WAN component to communicated with a WAN). Wireless links may also be implemented. In any such implementation, communication interface 1818 sends and receives electrical, electromagnetic or optical signals that carry digital data streams representing various types of information.
Network link 1820 typically provides data communication through one or more networks to other data devices. For example, network link 1820 may provide a connection through local network 1822 to a host computer 1824 or to data equipment operated by an Internet Service Provider (ISP) 1826. ISP 1826 in turn provides data communication services through the world wide packet data communication network now commonly referred to as the “Internet” 1828. Local network 1822 and Internet 1828 both use electrical, electromagnetic or optical signals that carry digital data streams. The signals through the various networks and the signals on network link 1820 and through communication interface 1818, which carry the digital data to and from computer system 1800, are example forms of transmission media.
Computer system 1800 can send messages and receive data, including program code, through the network(s), network link 1820 and communication interface 1818. In the Internet example, a server 1830 might transmit a requested code for an application program through Internet 1828, ISP 1826, local network 1822 and communication interface 1818.
The received code may be executed by processor 1804 as it is received, and/or stored in storage device 1810, or other non-volatile storage for later execution.
Each of the processes, methods, and algorithms described in the preceding sections may be embodied in, and fully or partially automated by, code modules executed by one or more computer systems or computer processors comprising computer hardware. The processes and algorithms may be implemented partially or wholly in application-specific circuitry.
The various features and processes described above may be used independently of one another, or may be combined in various ways. All possible combinations and subcombinations are intended to fall within the scope of this disclosure. In addition, certain method or process blocks may be omitted in some implementations. The methods and processes described herein are also not limited to any particular sequence, and the blocks or states relating thereto can be performed in other sequences that are appropriate. For example, described blocks or states may be performed in an order other than that specifically disclosed, or multiple blocks or states may be combined in a single block or state. The example blocks or states may be performed in serial, in parallel, or in some other manner. Blocks or states may be added to or removed from the disclosed example embodiments. The example systems and components described herein may be configured differently than described. For example, elements may be added to, removed from, or rearranged compared to the disclosed example embodiments.
Conditional language, such as, among others, “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments include, while other embodiments do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without user input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular embodiment.
Any process descriptions, elements, or blocks in the flow diagrams described herein and/or depicted in the attached figures should be understood as potentially representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps in the process. Alternate implementations are included within the scope of the embodiments described herein in which elements or functions may be deleted, executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those skilled in the art.
It should be emphasized that many variations and modifications may be made to the above-described embodiments, the elements of which are to be understood as being among other acceptable examples. All such modifications and variations are intended to be included herein within the scope of this disclosure. The foregoing description details certain embodiments of the invention. It will be appreciated, however, that no matter how detailed the foregoing appears in text, the invention can be practiced in many ways. As is also stated above, it should be noted that the use of particular terminology when describing certain features or aspects of the invention should not be taken to imply that the terminology is being re-defined herein to be restricted to including any specific characteristics of the features or aspects of the invention with which that terminology is associated. The scope of the invention should therefore be construed in accordance with the appended claims and any equivalents thereof.
This application is a continuation of U.S. application Ser. No. 14/581,823, filed Dec. 23, 2014, which application is a continuation of U.S. application Ser. No. 14/108,187, filed Dec. 16, 2013, which claims the benefit of U.S. Provisional Application No. 61/893,058, filed Oct. 18, 2013, the entire content of which is incorporated herein by reference. Any and all applications for which a foreign or domestic priority claim is identified in the Application Data Sheet as filed with the present application are hereby incorporated by reference under 37 CFR 1.57.
Number | Name | Date | Kind |
---|---|---|---|
4899161 | Morin et al. | Feb 1990 | A |
4958305 | Piazza | Sep 1990 | A |
5109399 | Thompson | Apr 1992 | A |
5329108 | Lamoure | Jul 1994 | A |
5632009 | Rao et al. | May 1997 | A |
5670987 | Doi et al. | Sep 1997 | A |
5754182 | Kobayashi | May 1998 | A |
5781195 | Marvin | Jul 1998 | A |
5781704 | Rossmo | Jul 1998 | A |
5798769 | Chiu et al. | Aug 1998 | A |
5845300 | Comer | Dec 1998 | A |
6057757 | Arrowsmith et al. | May 2000 | A |
6091956 | Hollenberg | Jul 2000 | A |
6157747 | Szeliski et al. | Dec 2000 | A |
6161098 | Wallman | Dec 2000 | A |
6173067 | Payton et al. | Jan 2001 | B1 |
6178432 | Cook et al. | Jan 2001 | B1 |
6219053 | Tachibana et al. | Apr 2001 | B1 |
6232971 | Haynes | May 2001 | B1 |
6247019 | Davies | Jun 2001 | B1 |
6279018 | Kudrolli et al. | Aug 2001 | B1 |
6341310 | Leshem et al. | Jan 2002 | B1 |
6366933 | Ball et al. | Apr 2002 | B1 |
6369835 | Lin | Apr 2002 | B1 |
6389289 | Voce et al. | May 2002 | B1 |
6414683 | Gueziec | Jul 2002 | B1 |
6456997 | Shukla | Sep 2002 | B1 |
6483509 | Rabenhorst | Nov 2002 | B1 |
6529900 | Patterson et al. | Mar 2003 | B1 |
6549944 | Weinberg et al. | Apr 2003 | B1 |
6560620 | Ching | May 2003 | B1 |
6581068 | Bensoussan et al. | Jun 2003 | B1 |
6594672 | Lampson et al. | Jul 2003 | B1 |
6631496 | Li et al. | Oct 2003 | B1 |
6642945 | Sharpe | Nov 2003 | B1 |
6662103 | Skolnick et al. | Dec 2003 | B1 |
6674434 | Chojnacki et al. | Jan 2004 | B1 |
6714936 | Nevin, III | Mar 2004 | B1 |
6757445 | Knopp | Jun 2004 | B1 |
6775675 | Nwabueze et al. | Aug 2004 | B1 |
6828920 | Owen et al. | Dec 2004 | B2 |
6839745 | Dingari et al. | Jan 2005 | B1 |
6877137 | Rivette et al. | Apr 2005 | B1 |
6976210 | Silva et al. | Dec 2005 | B1 |
6980984 | Huffman et al. | Dec 2005 | B1 |
6985950 | Hanson et al. | Jan 2006 | B1 |
7036085 | Barros | Apr 2006 | B2 |
7043702 | Chi et al. | May 2006 | B2 |
7055110 | Kupka et al. | May 2006 | B2 |
7139800 | Bellotti et al. | Nov 2006 | B2 |
7158878 | Rasmussen et al. | Jan 2007 | B2 |
7162475 | Ackerman | Jan 2007 | B2 |
7168039 | Bertram | Jan 2007 | B2 |
7171427 | Witowski et al. | Jan 2007 | B2 |
7269786 | Malloy et al. | Sep 2007 | B1 |
7278105 | Kitts | Oct 2007 | B1 |
7290698 | Poslinski et al. | Nov 2007 | B2 |
7333998 | Heckerman et al. | Feb 2008 | B2 |
7370047 | Gorman | May 2008 | B2 |
7375732 | Arcas | May 2008 | B2 |
7379811 | Rasmussen et al. | May 2008 | B2 |
7379903 | Caballero et al. | May 2008 | B2 |
7426654 | Adams et al. | Sep 2008 | B2 |
7454466 | Bellotti et al. | Nov 2008 | B2 |
7457706 | Malero et al. | Nov 2008 | B2 |
7467375 | Tondreau et al. | Dec 2008 | B2 |
7487139 | Fraleigh et al. | Feb 2009 | B2 |
7502786 | Liu et al. | Mar 2009 | B2 |
7519470 | Brasche et al. | Apr 2009 | B2 |
7525422 | Bishop et al. | Apr 2009 | B2 |
7529195 | Gorman | May 2009 | B2 |
7529727 | Arning et al. | May 2009 | B2 |
7529734 | Dirisala | May 2009 | B2 |
7539666 | Ashworth et al. | May 2009 | B2 |
7546245 | Surpin et al. | Jun 2009 | B2 |
7558677 | Jones | Jul 2009 | B2 |
7574409 | Patinkin | Aug 2009 | B2 |
7574428 | Leiserowitz et al. | Aug 2009 | B2 |
7579965 | Bucholz | Aug 2009 | B2 |
7596285 | Brown et al. | Sep 2009 | B2 |
7614006 | Molander | Nov 2009 | B2 |
7617232 | Gabbert et al. | Nov 2009 | B2 |
7620628 | Kapur et al. | Nov 2009 | B2 |
7627812 | Chamberlain et al. | Dec 2009 | B2 |
7634717 | Chamberlain et al. | Dec 2009 | B2 |
7640173 | Surpin et al. | Dec 2009 | B2 |
7663621 | Allen et al. | Feb 2010 | B1 |
7703021 | Flam | Apr 2010 | B1 |
7706817 | Bamrah et al. | Apr 2010 | B2 |
7712049 | Williams et al. | May 2010 | B2 |
7716067 | Surpin et al. | May 2010 | B2 |
7716077 | Mikurak | May 2010 | B1 |
7725530 | Sah et al. | May 2010 | B2 |
7725547 | Albertson et al. | May 2010 | B2 |
7730082 | Sah et al. | Jun 2010 | B2 |
7730109 | Rohrs et al. | Jun 2010 | B2 |
7770100 | Chamberlain et al. | Aug 2010 | B2 |
7791616 | Ioup et al. | Sep 2010 | B2 |
7805457 | Viola et al. | Sep 2010 | B1 |
7809703 | Balabhadrapatruni et al. | Oct 2010 | B2 |
7818658 | Chen | Oct 2010 | B2 |
7870493 | Pall et al. | Jan 2011 | B2 |
7872647 | Mayer et al. | Jan 2011 | B2 |
7894984 | Rasmussen et al. | Feb 2011 | B2 |
7899611 | Downs et al. | Mar 2011 | B2 |
7917376 | Bellin et al. | Mar 2011 | B2 |
7920963 | Jouline et al. | Apr 2011 | B2 |
7933862 | Chamberlain et al. | Apr 2011 | B2 |
7945852 | Pilskains | May 2011 | B1 |
7962281 | Rasmussen et al. | Jun 2011 | B2 |
7962495 | Jain et al. | Jun 2011 | B2 |
7962848 | Bertram | Jun 2011 | B2 |
7970240 | Chao et al. | Jun 2011 | B1 |
7971150 | Raskutti et al. | Jun 2011 | B2 |
7984374 | Caro et al. | Jul 2011 | B2 |
8001465 | Kudrolli et al. | Aug 2011 | B2 |
8001482 | Bhattiprolu et al. | Aug 2011 | B2 |
8010545 | Stefik et al. | Aug 2011 | B2 |
8010886 | Gusmorino et al. | Aug 2011 | B2 |
8015487 | Roy et al. | Sep 2011 | B2 |
8019709 | Norton et al. | Sep 2011 | B2 |
8024778 | Cash et al. | Sep 2011 | B2 |
8036632 | Cona et al. | Oct 2011 | B1 |
8065080 | Koch | Nov 2011 | B2 |
8082172 | Chao et al. | Dec 2011 | B2 |
8085268 | Carrino et al. | Dec 2011 | B2 |
8103543 | Zwicky | Jan 2012 | B1 |
8134457 | Velipasalar et al. | Mar 2012 | B2 |
8145703 | Frishert et al. | Mar 2012 | B2 |
8185819 | Sah et al. | May 2012 | B2 |
8214361 | Sandler et al. | Jul 2012 | B1 |
8214764 | Gemmell et al. | Jul 2012 | B2 |
8225201 | Michael | Jul 2012 | B2 |
8229947 | Fujinaga | Jul 2012 | B2 |
8230333 | Decherd et al. | Jul 2012 | B2 |
8271461 | Pike et al. | Sep 2012 | B2 |
8280880 | Aymeloglu et al. | Oct 2012 | B1 |
8290926 | Ozzie et al. | Oct 2012 | B2 |
8290942 | Jones et al. | Oct 2012 | B2 |
8301464 | Cave et al. | Oct 2012 | B1 |
8301904 | Gryaznov | Oct 2012 | B1 |
8312367 | Foster | Nov 2012 | B2 |
8312546 | Alme | Nov 2012 | B2 |
8325178 | Doyle, Jr. | Dec 2012 | B1 |
8352881 | Champion et al. | Jan 2013 | B2 |
8368695 | Howell et al. | Feb 2013 | B2 |
8397171 | Klassen et al. | Mar 2013 | B2 |
8400448 | Doyle, Jr. | Mar 2013 | B1 |
8407180 | Ramesh et al. | Mar 2013 | B1 |
8411046 | Kruzeniski et al. | Apr 2013 | B2 |
8412234 | Gatmir-Motahari et al. | Apr 2013 | B1 |
8412707 | Mianji | Apr 2013 | B1 |
8422825 | Neophytou et al. | Apr 2013 | B1 |
8447722 | Ahuja et al. | May 2013 | B1 |
8452790 | Mianji | May 2013 | B1 |
8463036 | Ramesh et al. | Jun 2013 | B1 |
8489331 | Kopf et al. | Jul 2013 | B2 |
8489641 | Seefeld et al. | Jul 2013 | B1 |
8498984 | Hwang et al. | Jul 2013 | B1 |
8508533 | Cervelli et al. | Aug 2013 | B2 |
8510743 | Hackborn et al. | Aug 2013 | B2 |
8514082 | Cova et al. | Aug 2013 | B2 |
8514229 | Cervelli et al. | Aug 2013 | B2 |
8515207 | Chau | Aug 2013 | B2 |
8554579 | Tribble et al. | Oct 2013 | B2 |
8554653 | Falkenborg et al. | Oct 2013 | B2 |
8554709 | Goodson et al. | Oct 2013 | B2 |
8554840 | Milgramm | Oct 2013 | B1 |
8564596 | Carrino et al. | Oct 2013 | B2 |
8577911 | Stepinski et al. | Nov 2013 | B1 |
8589273 | Creeden et al. | Nov 2013 | B2 |
8595234 | Siripuapu et al. | Nov 2013 | B2 |
8620641 | Farnsworth et al. | Dec 2013 | B2 |
8639757 | Zang et al. | Jan 2014 | B1 |
8646080 | Williamson et al. | Feb 2014 | B2 |
8676597 | Buehler et al. | Mar 2014 | B2 |
8676857 | Adams et al. | Mar 2014 | B1 |
8689108 | Duffield et al. | Apr 2014 | B1 |
8707185 | Robinson et al. | Apr 2014 | B2 |
8713467 | Goldenberg et al. | Apr 2014 | B1 |
8726379 | Stiansen et al. | May 2014 | B1 |
8739278 | Varghese | May 2014 | B2 |
8742934 | Sarpy et al. | Jun 2014 | B1 |
8745516 | Mason et al. | Jun 2014 | B2 |
8756224 | Dassa et al. | Jun 2014 | B2 |
8756244 | Dassa et al. | Jun 2014 | B2 |
8768009 | Smith | Jul 2014 | B1 |
8781169 | Jackson et al. | Jul 2014 | B2 |
8787939 | Papakipos et al. | Jul 2014 | B2 |
8799799 | Cervelli et al. | Aug 2014 | B1 |
8799812 | Parker | Aug 2014 | B2 |
8812960 | Sun et al. | Aug 2014 | B1 |
8830322 | Nerayoff et al. | Sep 2014 | B2 |
8832594 | Thompson et al. | Sep 2014 | B1 |
8868486 | Tamayo | Oct 2014 | B2 |
8868537 | Colgrove et al. | Oct 2014 | B1 |
8917274 | Ma et al. | Dec 2014 | B2 |
8924872 | Bogomolov et al. | Dec 2014 | B1 |
8937619 | Sharma et al. | Jan 2015 | B2 |
8938686 | Erenrich et al. | Jan 2015 | B1 |
9009171 | Grossman et al. | Apr 2015 | B1 |
9009827 | Albertson et al. | Apr 2015 | B1 |
9021260 | Falk et al. | Apr 2015 | B1 |
9021384 | Beard et al. | Apr 2015 | B1 |
9043696 | Meiklejohn et al. | May 2015 | B1 |
9043894 | Dennison et al. | May 2015 | B1 |
10042524 | Bogomolov et al. | Aug 2018 | B2 |
20010021936 | Bertram | Sep 2001 | A1 |
20020003539 | Abe | Jan 2002 | A1 |
20020033848 | Sciammarella et al. | Mar 2002 | A1 |
20020065708 | Senay et al. | May 2002 | A1 |
20020091707 | Keller | Jul 2002 | A1 |
20020095658 | Shulman | Jul 2002 | A1 |
20020116120 | Ruiz et al. | Aug 2002 | A1 |
20020130867 | Yang et al. | Sep 2002 | A1 |
20020130907 | Chi et al. | Sep 2002 | A1 |
20020174201 | Ramer et al. | Nov 2002 | A1 |
20020194119 | Wright et al. | Dec 2002 | A1 |
20030028560 | Kudrolli et al. | Feb 2003 | A1 |
20030039948 | Donahue | Feb 2003 | A1 |
20030052896 | Higgins et al. | Mar 2003 | A1 |
20030103049 | Kindratenko et al. | Jun 2003 | A1 |
20030140106 | Raguseo | Jul 2003 | A1 |
20030144868 | MacIntyre et al. | Jul 2003 | A1 |
20030163352 | Surpin et al. | Aug 2003 | A1 |
20030200217 | Ackerman | Oct 2003 | A1 |
20030225755 | Iwayama et al. | Dec 2003 | A1 |
20030229848 | Arend et al. | Dec 2003 | A1 |
20040030492 | Fox et al. | Feb 2004 | A1 |
20040032432 | Baynger | Feb 2004 | A1 |
20040039498 | Ollis et al. | Feb 2004 | A1 |
20040064256 | Barinek et al. | Apr 2004 | A1 |
20040085318 | Hassler et al. | May 2004 | A1 |
20040095349 | Bito et al. | May 2004 | A1 |
20040098236 | Mayer et al. | May 2004 | A1 |
20040111410 | Burgoon et al. | Jun 2004 | A1 |
20040126840 | Cheng et al. | Jul 2004 | A1 |
20040143602 | Ruiz et al. | Jul 2004 | A1 |
20040143796 | Lerner et al. | Jul 2004 | A1 |
20040163039 | Gorman | Aug 2004 | A1 |
20040181554 | Heckerman et al. | Sep 2004 | A1 |
20040193600 | Kaasten et al. | Sep 2004 | A1 |
20040194549 | Noel | Oct 2004 | A1 |
20040210847 | Berson et al. | Oct 2004 | A1 |
20040221223 | Yu et al. | Nov 2004 | A1 |
20040260702 | Cragun et al. | Dec 2004 | A1 |
20040267746 | Marcjan et al. | Dec 2004 | A1 |
20050027705 | Sadri et al. | Feb 2005 | A1 |
20050028094 | Allyn | Feb 2005 | A1 |
20050031197 | Knopp | Feb 2005 | A1 |
20050034062 | Bufkin et al. | Feb 2005 | A1 |
20050039119 | Parks et al. | Feb 2005 | A1 |
20050065811 | Chu et al. | Mar 2005 | A1 |
20050080769 | Gemmell | Apr 2005 | A1 |
20050086207 | Heuer et al. | Apr 2005 | A1 |
20050125715 | Di Franco et al. | Jun 2005 | A1 |
20050162523 | Darrell et al. | Jul 2005 | A1 |
20050166144 | Gross | Jul 2005 | A1 |
20050180330 | Shapiro | Aug 2005 | A1 |
20050182502 | Iyengar | Aug 2005 | A1 |
20050182793 | Keenan et al. | Aug 2005 | A1 |
20050183005 | Denoue et al. | Aug 2005 | A1 |
20050210409 | Jou | Sep 2005 | A1 |
20050246327 | Yeung et al. | Nov 2005 | A1 |
20050251786 | Citron et al. | Nov 2005 | A1 |
20050267652 | Allstadt et al. | Dec 2005 | A1 |
20060026120 | Carolan et al. | Feb 2006 | A1 |
20060026170 | Kreitler et al. | Feb 2006 | A1 |
20060045470 | Poslinski et al. | Mar 2006 | A1 |
20060059139 | Robinson | Mar 2006 | A1 |
20060074866 | Chamberlain et al. | Apr 2006 | A1 |
20060074881 | Vembu et al. | Apr 2006 | A1 |
20060080619 | Carlson et al. | Apr 2006 | A1 |
20060129746 | Porter | Jun 2006 | A1 |
20060139375 | Rasmussen et al. | Jun 2006 | A1 |
20060142949 | Helt | Jun 2006 | A1 |
20060146050 | Yamauchi | Jul 2006 | A1 |
20060149596 | Surpin et al. | Jul 2006 | A1 |
20060203337 | White | Sep 2006 | A1 |
20060218637 | Thomas et al. | Sep 2006 | A1 |
20060241974 | Chao et al. | Oct 2006 | A1 |
20060242040 | Rader | Oct 2006 | A1 |
20060242630 | Koike et al. | Oct 2006 | A1 |
20060251307 | Florin et al. | Nov 2006 | A1 |
20060271277 | Hu et al. | Nov 2006 | A1 |
20060279630 | Aggarwal et al. | Dec 2006 | A1 |
20070011150 | Frank | Jan 2007 | A1 |
20070016363 | Huang et al. | Jan 2007 | A1 |
20070024620 | Muller-Fischer et al. | Feb 2007 | A1 |
20070038962 | Fuchs et al. | Feb 2007 | A1 |
20070057966 | Ohno et al. | Mar 2007 | A1 |
20070078832 | Ott et al. | Apr 2007 | A1 |
20070083541 | Fraleigh et al. | Apr 2007 | A1 |
20070094389 | Nussey et al. | Apr 2007 | A1 |
20070150369 | Zivin | Jun 2007 | A1 |
20070174760 | Chamberlain et al. | Jul 2007 | A1 |
20070188516 | Loup et al. | Aug 2007 | A1 |
20070192265 | Chopin et al. | Aug 2007 | A1 |
20070198571 | Ferguson et al. | Aug 2007 | A1 |
20070208497 | Downs et al. | Sep 2007 | A1 |
20070208498 | Barker et al. | Sep 2007 | A1 |
20070208681 | Bucholz | Sep 2007 | A1 |
20070208736 | Tanigawa et al. | Sep 2007 | A1 |
20070240062 | Christena et al. | Oct 2007 | A1 |
20070258642 | Thota | Nov 2007 | A1 |
20070266336 | Nojima et al. | Nov 2007 | A1 |
20070294643 | Kyle | Dec 2007 | A1 |
20080010605 | Frank | Jan 2008 | A1 |
20080016216 | Worley et al. | Jan 2008 | A1 |
20080040684 | Crump | Feb 2008 | A1 |
20080051989 | Welsh | Feb 2008 | A1 |
20080052142 | Bailey et al. | Feb 2008 | A1 |
20080077597 | Butler | Mar 2008 | A1 |
20080077642 | Carbone et al. | Mar 2008 | A1 |
20080082578 | Hogue et al. | Apr 2008 | A1 |
20080098085 | Krane et al. | Apr 2008 | A1 |
20080104019 | Nath | May 2008 | A1 |
20080126951 | Sood et al. | May 2008 | A1 |
20080155440 | Trevor et al. | Jun 2008 | A1 |
20080162616 | Gross et al. | Jul 2008 | A1 |
20080163073 | Becker et al. | Jul 2008 | A1 |
20080192053 | Howell et al. | Aug 2008 | A1 |
20080195417 | Surpin et al. | Aug 2008 | A1 |
20080195608 | Clover | Aug 2008 | A1 |
20080222295 | Robinson et al. | Sep 2008 | A1 |
20080223834 | Griffiths et al. | Sep 2008 | A1 |
20080228512 | Calkins et al. | Sep 2008 | A1 |
20080229056 | Agarwal et al. | Sep 2008 | A1 |
20080255973 | El Wade et al. | Oct 2008 | A1 |
20080263468 | Cappione et al. | Oct 2008 | A1 |
20080267107 | Rosenberg | Oct 2008 | A1 |
20080270468 | Mao | Oct 2008 | A1 |
20080276167 | Michael | Nov 2008 | A1 |
20080278311 | Grange et al. | Nov 2008 | A1 |
20080288306 | MacIntyre et al. | Nov 2008 | A1 |
20080294678 | Gorman et al. | Nov 2008 | A1 |
20080301643 | Appleton et al. | Dec 2008 | A1 |
20090002492 | Velipasalar et al. | Jan 2009 | A1 |
20090027418 | Maru et al. | Jan 2009 | A1 |
20090030915 | Winter et al. | Jan 2009 | A1 |
20090055251 | Shah et al. | Feb 2009 | A1 |
20090076845 | Bellin et al. | Mar 2009 | A1 |
20090088964 | Schaaf et al. | Apr 2009 | A1 |
20090100018 | Roberts | Apr 2009 | A1 |
20090115786 | Shmiasaki et al. | May 2009 | A1 |
20090119309 | Gibson et al. | May 2009 | A1 |
20090125369 | Kloosstra et al. | May 2009 | A1 |
20090125459 | Norton et al. | May 2009 | A1 |
20090132921 | Hwangbo et al. | May 2009 | A1 |
20090132953 | Reed et al. | May 2009 | A1 |
20090143052 | Bates et al. | Jun 2009 | A1 |
20090144262 | White et al. | Jun 2009 | A1 |
20090144274 | Fraleigh et al. | Jun 2009 | A1 |
20090158185 | Lacevic et al. | Jun 2009 | A1 |
20090164934 | Bhattiprolu et al. | Jun 2009 | A1 |
20090171939 | Athsani et al. | Jul 2009 | A1 |
20090172511 | Decherd et al. | Jul 2009 | A1 |
20090177962 | Gusmorino et al. | Jul 2009 | A1 |
20090179892 | Tsuda et al. | Jul 2009 | A1 |
20090187464 | Bai et al. | Jul 2009 | A1 |
20090222400 | Kupershmidt et al. | Sep 2009 | A1 |
20090222760 | Halverson et al. | Sep 2009 | A1 |
20090234720 | George et al. | Sep 2009 | A1 |
20090249244 | Robinson et al. | Oct 2009 | A1 |
20090281839 | Lynn et al. | Nov 2009 | A1 |
20090287470 | Farnsworth et al. | Nov 2009 | A1 |
20090292626 | Oxford | Nov 2009 | A1 |
20100011282 | Dollard et al. | Jan 2010 | A1 |
20100042922 | Bradateanu et al. | Feb 2010 | A1 |
20100057716 | Stefik et al. | Mar 2010 | A1 |
20100063961 | Guiheneuf et al. | Mar 2010 | A1 |
20100070523 | Delgo et al. | Mar 2010 | A1 |
20100070842 | Aymeloglu et al. | Mar 2010 | A1 |
20100070845 | Facemire et al. | Mar 2010 | A1 |
20100070897 | Aymeloglu et al. | Mar 2010 | A1 |
20100076968 | Boyns et al. | Mar 2010 | A1 |
20100100963 | Mahaffey | Apr 2010 | A1 |
20100103124 | Kruzeniski et al. | Apr 2010 | A1 |
20100106420 | Mattikalli et al. | Apr 2010 | A1 |
20100114887 | Conway et al. | May 2010 | A1 |
20100122152 | Chamberlain et al. | May 2010 | A1 |
20100131457 | Heimendinger | May 2010 | A1 |
20100162176 | Dunton | Jun 2010 | A1 |
20100191563 | Schlaifer et al. | Jul 2010 | A1 |
20100198684 | Eraker et al. | Aug 2010 | A1 |
20100199225 | Coleman et al. | Aug 2010 | A1 |
20100228812 | Uomini | Sep 2010 | A1 |
20100250412 | Wagner | Sep 2010 | A1 |
20100280857 | Liu et al. | Nov 2010 | A1 |
20100293174 | Bennett et al. | Nov 2010 | A1 |
20100306713 | Geisner et al. | Dec 2010 | A1 |
20100313119 | Baldwin et al. | Dec 2010 | A1 |
20100318924 | Frankel et al. | Dec 2010 | A1 |
20100321399 | Ellren et al. | Dec 2010 | A1 |
20100325526 | Ellis et al. | Dec 2010 | A1 |
20100325581 | Finkelstein et al. | Dec 2010 | A1 |
20100330801 | Rouh | Dec 2010 | A1 |
20110022312 | McDonough et al. | Jan 2011 | A1 |
20110029526 | Knight et al. | Feb 2011 | A1 |
20110047159 | Baid et al. | Feb 2011 | A1 |
20110060753 | Shaked et al. | Mar 2011 | A1 |
20110061013 | Bilicki et al. | Mar 2011 | A1 |
20110074811 | Hanson et al. | Mar 2011 | A1 |
20110078055 | Faribault et al. | Mar 2011 | A1 |
20110078173 | Seligmann et al. | Mar 2011 | A1 |
20110093327 | Fordyce, III et al. | Apr 2011 | A1 |
20110106781 | Pearson | May 2011 | A1 |
20110117878 | Barash et al. | May 2011 | A1 |
20110119100 | Ruhl et al. | May 2011 | A1 |
20110137766 | Rasmussen et al. | Jun 2011 | A1 |
20110153384 | Horne et al. | Jun 2011 | A1 |
20110161096 | Buehler et al. | Jun 2011 | A1 |
20110167105 | Ramakrishnan et al. | Jul 2011 | A1 |
20110170799 | Carrino et al. | Jul 2011 | A1 |
20110173032 | Payne et al. | Jul 2011 | A1 |
20110185316 | Reid et al. | Jul 2011 | A1 |
20110208724 | Jones et al. | Aug 2011 | A1 |
20110218934 | Elser | Sep 2011 | A1 |
20110219450 | McDougal et al. | Sep 2011 | A1 |
20110225198 | Edwards et al. | Sep 2011 | A1 |
20110238553 | Raj et al. | Sep 2011 | A1 |
20110258158 | Resende et al. | Oct 2011 | A1 |
20110270705 | Parker | Nov 2011 | A1 |
20110289397 | Eastmond et al. | Nov 2011 | A1 |
20110289407 | Naik et al. | Nov 2011 | A1 |
20110289420 | Morioka et al. | Nov 2011 | A1 |
20110291851 | Whisenant | Dec 2011 | A1 |
20110310005 | Chen et al. | Dec 2011 | A1 |
20110314007 | Dassa et al. | Dec 2011 | A1 |
20120019559 | Siler et al. | Jan 2012 | A1 |
20120036013 | Neuhaus et al. | Feb 2012 | A1 |
20120036434 | Oberstein | Feb 2012 | A1 |
20120050293 | Carlhian et al. | Mar 2012 | A1 |
20120066296 | Appleton et al. | Mar 2012 | A1 |
20120072825 | Sherkin et al. | Mar 2012 | A1 |
20120079363 | Folting et al. | Mar 2012 | A1 |
20120084118 | Bai et al. | Apr 2012 | A1 |
20120105632 | Renkis | May 2012 | A1 |
20120106801 | Jackson | May 2012 | A1 |
20120117082 | Koperda et al. | May 2012 | A1 |
20120131512 | Takeuchi et al. | May 2012 | A1 |
20120144335 | Abeln et al. | Jun 2012 | A1 |
20120159307 | Chung et al. | Jun 2012 | A1 |
20120159362 | Brown et al. | Jun 2012 | A1 |
20120159363 | DeBacker et al. | Jun 2012 | A1 |
20120159399 | Bastide et al. | Jun 2012 | A1 |
20120170847 | Tsukidate | Jul 2012 | A1 |
20120173985 | Peppel | Jul 2012 | A1 |
20120196557 | Reich et al. | Aug 2012 | A1 |
20120196558 | Reich | Aug 2012 | A1 |
20120203708 | Psota et al. | Aug 2012 | A1 |
20120206469 | Hulubei et al. | Aug 2012 | A1 |
20120208636 | Feige | Aug 2012 | A1 |
20120221511 | Gibson et al. | Aug 2012 | A1 |
20120221553 | Wittmer et al. | Aug 2012 | A1 |
20120221580 | Barney | Aug 2012 | A1 |
20120245976 | Kumar et al. | Sep 2012 | A1 |
20120246148 | Dror | Sep 2012 | A1 |
20120254129 | Wheeler et al. | Oct 2012 | A1 |
20120284345 | Costenaro et al. | Nov 2012 | A1 |
20120290879 | Shibuya et al. | Nov 2012 | A1 |
20120296907 | Long et al. | Nov 2012 | A1 |
20120311684 | Paulsen et al. | Dec 2012 | A1 |
20120323888 | Osann, Jr. | Dec 2012 | A1 |
20120330973 | Ghuneim et al. | Dec 2012 | A1 |
20130006426 | Healey et al. | Jan 2013 | A1 |
20130006725 | Simanek et al. | Jan 2013 | A1 |
20130006916 | McBride et al. | Jan 2013 | A1 |
20130018796 | Kolhatkar et al. | Jan 2013 | A1 |
20130021445 | Cossette-Pacheco et al. | Jan 2013 | A1 |
20130024202 | Harris et al. | Jan 2013 | A1 |
20130046635 | Grigg et al. | Feb 2013 | A1 |
20130046842 | Muntz et al. | Feb 2013 | A1 |
20130060786 | Serrano et al. | Mar 2013 | A1 |
20130061169 | Pearcy | Mar 2013 | A1 |
20130073377 | Heath | Mar 2013 | A1 |
20130073454 | Busch | Mar 2013 | A1 |
20130076732 | Cervelli et al. | Mar 2013 | A1 |
20130078943 | Biage et al. | Mar 2013 | A1 |
20130097482 | Marantz et al. | Apr 2013 | A1 |
20130100134 | Cervelli et al. | Apr 2013 | A1 |
20130101159 | Chao et al. | Apr 2013 | A1 |
20130110822 | Ikeda et al. | May 2013 | A1 |
20130110877 | Bonham et al. | May 2013 | A1 |
20130111320 | Campbell et al. | May 2013 | A1 |
20130117651 | Waldman et al. | May 2013 | A1 |
20130150004 | Rosen | Jun 2013 | A1 |
20130151148 | Parundekar et al. | Jun 2013 | A1 |
20130151388 | Falkenborg et al. | Jun 2013 | A1 |
20130157234 | Gulli et al. | Jun 2013 | A1 |
20130166550 | Buchmann et al. | Jun 2013 | A1 |
20130176321 | Mitchell et al. | Jul 2013 | A1 |
20130179420 | Park et al. | Jul 2013 | A1 |
20130224696 | Wolfe et al. | Aug 2013 | A1 |
20130226953 | Markovich et al. | Aug 2013 | A1 |
20130238616 | Rose et al. | Sep 2013 | A1 |
20130246170 | Gross et al. | Sep 2013 | A1 |
20130251233 | Yang et al. | Sep 2013 | A1 |
20130262527 | Hunter et al. | Oct 2013 | A1 |
20130263019 | Castellanos et al. | Oct 2013 | A1 |
20130267207 | Hao et al. | Oct 2013 | A1 |
20130268520 | Fisher et al. | Oct 2013 | A1 |
20130279757 | Kephart | Oct 2013 | A1 |
20130282696 | John et al. | Oct 2013 | A1 |
20130282723 | Petersen et al. | Oct 2013 | A1 |
20130290011 | Lynn et al. | Oct 2013 | A1 |
20130290825 | Arndt et al. | Oct 2013 | A1 |
20130297619 | Chandrasekaran et al. | Nov 2013 | A1 |
20130311375 | Priebatsch | Nov 2013 | A1 |
20140019936 | Cohanoff | Jan 2014 | A1 |
20140032506 | Hoey et al. | Jan 2014 | A1 |
20140033010 | Richardt et al. | Jan 2014 | A1 |
20140040371 | Gurevich et al. | Feb 2014 | A1 |
20140047357 | Alfaro et al. | Feb 2014 | A1 |
20140059038 | McPherson et al. | Feb 2014 | A1 |
20140067611 | Adachi et al. | Mar 2014 | A1 |
20140068487 | Steiger et al. | Mar 2014 | A1 |
20140095273 | Tang et al. | Apr 2014 | A1 |
20140095509 | Patton | Apr 2014 | A1 |
20140108068 | Williams | Apr 2014 | A1 |
20140108380 | Gotz et al. | Apr 2014 | A1 |
20140108985 | Scott et al. | Apr 2014 | A1 |
20140129261 | Bothwell et al. | May 2014 | A1 |
20140149436 | Bahrami et al. | May 2014 | A1 |
20140156527 | Grigg et al. | Jun 2014 | A1 |
20140157172 | Peery et al. | Jun 2014 | A1 |
20140164502 | Khodorenko et al. | Jun 2014 | A1 |
20140188847 | Tang et al. | Jul 2014 | A1 |
20140189536 | Lange et al. | Jul 2014 | A1 |
20140195515 | Baker et al. | Jul 2014 | A1 |
20140195887 | Ellis et al. | Jul 2014 | A1 |
20140267294 | Ma | Sep 2014 | A1 |
20140267295 | Sharma | Sep 2014 | A1 |
20140279824 | Tamayo | Sep 2014 | A1 |
20140316911 | Gross | Oct 2014 | A1 |
20140333651 | Cervelli et al. | Nov 2014 | A1 |
20140337772 | Cervelli et al. | Nov 2014 | A1 |
20140344230 | Krause et al. | Nov 2014 | A1 |
20140361899 | Layson | Dec 2014 | A1 |
20150019394 | Unser et al. | Jan 2015 | A1 |
20150029176 | Baxter et al. | Jan 2015 | A1 |
20150046870 | Goldenberg et al. | Feb 2015 | A1 |
20150089424 | Duffield et al. | Mar 2015 | A1 |
20150100897 | Sun et al. | Apr 2015 | A1 |
20150100907 | Erenrich et al. | Apr 2015 | A1 |
20150134666 | Gattiker et al. | May 2015 | A1 |
20150169709 | Kara et al. | Jun 2015 | A1 |
20150169726 | Kara et al. | Jun 2015 | A1 |
20150170077 | Kara et al. | Jun 2015 | A1 |
20150178877 | Bogomolov et al. | Jun 2015 | A1 |
20150186821 | Wang et al. | Jul 2015 | A1 |
20150187036 | Wang et al. | Jul 2015 | A1 |
Number | Date | Country |
---|---|---|
2014250678 | Oct 2015 | AU |
102014103482 | Sep 2014 | DE |
102013222023 | Jan 2015 | DE |
102014215621 | Feb 2015 | DE |
0 763 201 | Mar 1997 | EP |
1672527 | Jun 2006 | EP |
2551799 | Jan 2013 | EP |
2560134 | Feb 2013 | EP |
2 575 107 | Apr 2013 | EP |
2778913 | Sep 2014 | EP |
2778977 | Sep 2014 | EP |
2778983 | Sep 2014 | EP |
2779082 | Sep 2014 | EP |
2835745 | Feb 2015 | EP |
2835770 | Feb 2015 | EP |
2838039 | Feb 2015 | EP |
2846241 | Mar 2015 | EP |
2851852 | Mar 2015 | EP |
2858014 | Apr 2015 | EP |
2858018 | Apr 2015 | EP |
2863326 | Apr 2015 | EP |
2863346 | Apr 2015 | EP |
2869211 | May 2015 | EP |
2881868 | Jun 2015 | EP |
2884439 | Jun 2015 | EP |
2884440 | Jun 2015 | EP |
2891992 | Jul 2015 | EP |
2516155 | Jan 2015 | GB |
2518745 | Apr 2015 | GB |
2012778 | Nov 2014 | NL |
2013306 | Feb 2015 | NL |
624557 | Dec 2014 | NZ |
WO 95032424 | Nov 1995 | WO |
WO 2000009529 | Feb 2000 | WO |
WO 2002065353 | Aug 2002 | WO |
WO 2004057268 | Jul 2004 | WO |
WO 2005013200 | Feb 2005 | WO |
WO 2005104736 | Nov 2005 | WO |
WO 2008064207 | May 2008 | WO |
WO 2009061501 | May 2009 | WO |
WO 2009123975 | Oct 2009 | WO |
WO 2010000014 | Jan 2010 | WO |
WO 2010030913 | Mar 2010 | WO |
WO 2011058507 | May 2011 | WO |
WO 2013010157 | Jan 2013 | WO |
WO 2013102892 | Jul 2013 | WO |
Entry |
---|
“A First Look: Predicting Market Demand for Food Retail using a Huff Analysis,” TRF Policy Solutions, Jul. 2012, pp. 30. |
“A Quick Guide to UniProtKB Swiss-Prot & TrEMBL,” Sep. 2011, pp. 2. |
“A Word About Banks and the Laundering of Drug Money,” Aug. 18, 2012, http://www.golemxiv.co.uk/2012/08/a-word-about-banks-and-the-laundering-of-drug-money/. |
“Andy Turner's GISRUK 2012 Notes” <https://docs.google.com/document/d/1cTmxg7mVx5gd89lqblCYvCEnHA4QAivH4l4WpyPsgE4/edit?pli=1> printed Sep. 16, 2013 in 15 pages. |
Acklen, Laura, “Absolute Beginner's Guide to Microsoft Word 2003,” Dec. 24, 2003, pp. 15-18, 34-41, 308-316. |
Amnet, “5 Great Tools for Visualizing Your Twitter Followers,” posted Aug. 4, 2010, http://www.amnetblog.com/component/content/article/115-5-grate-tools-for-visualizing-your-twitter-followers.html. |
Ananiev et al., “The New Modality API,” http://web.archive.org/web/20061211011958/http://java.sun.com/developer/technicalArticles/J2SE/Desktop/javase6/modality/ Jan. 21, 2006, pp. 8. |
Barnes et al., “Viewshed Analysis”, GIS-ARC/INFO 2001, <www.evsc.virginia.edu/˜jhp7e/evsc466/student_pres/Rounds.pdf>. |
Bluttman et al., “Excel Formulas and Functions for Dummies,” 2005, Wiley Publishing, Inc., pp. 280, 284-286. |
Boyce, Jim, “Microsoft Outlook 2010 Inside Out,” Aug. 1, 2010, retrieved from the internet https://capdtron.files.wordpress.com/2013/01/outlook-2010-inside_out.pdf. |
Bugzilla@Mozilla, “Bug 18726—[feature] Long-click means of invoking contextual menus not supported,” http://bugzilla.mozilla.org/show_bug.cgi?id=18726 printed Jun. 13, 2013 in 11 pages. |
Canese et al., “Chapter 2: PubMed: The Bibliographic Database,” The NCBI Handbook, Oct. 2002, pp. 1-10. |
Carver et al., “Real-Time Visibility Analysis and Rapid Viewshed Calculation Using a Voxel-Based Modelling Approach,” GISRUK 2012 Conference, Apr. 11-13, Lancaster UK, Apr. 13, 2012, pp. 6. |
Celik, Tantek, “CSS Basic User Interface Module Level 3 (CSS3 UI),” Section 8 Resizing and Overflow, Jan. 17, 2012, retrieved from internet http://www.w3.org/TR/2012/WD-css3-ui-20120117/#resizing-amp-overflow retrieved on May 18, 2015. |
Chen et al., “Bringing Order to the Web: Automatically Categorizing Search Results,” CHI 2000, Proceedings of the SIGCHI conference on Human Factors in Computing Systems, Apr. 1-6, 2000, The Hague, The Netherlands, pp. 145-152. |
Chung, Chin-Wan, “Dataplex: An Access to Heterogeneous Distributed Databases,” Communications of the ACM, Association for Computing Machinery, Inc., vol. 33, No. 1, Jan. 1, 1990, pp. 70-80. |
Conner, Nancy, “Google Apps: The Missing Manual,” May 1, 2008, pp. 15. |
Definition “Identify”, downloaded Jan. 22, 2015, 1 page. |
Definition “Overlay”, downloaded Jan. 22, 2015, 1 page. |
Delcher et al., “Identifying Bacterial Genes and Endosymbiont DNA with Glimmer,” BioInformatics, vol. 23, No. 6, 2007, pp. 673-679. |
Dramowicz, Ela, “Retail Trade Area Analysis Using the Huff Model,” Directions Magazine, Jul. 2, 2005 in 10 pages, http://www.directionsmag.com/articles/retail-trade-area-analysis-using-the-huff-model/123411. |
“The FASTA Program Package,” fasta-36.3.4, Mar. 25, 2011, pp. 29. |
Ghosh, P., “A Solution of Polygon Containment, Spatial Planning, and Other Related Problems Using Minkowski Operations,” Computer Vision, Graphics, and Image Processing, 1990, vol. 49, pp. 1-35. |
GIS-Net 3 Public_Department of Regional Planning. Planning & Zoning Information for Unincorporated LA County. Retrieved Oct. 2, 2013 from http://gis.planning.lacounty.gov/GIS-NET3_Public/Viewer.html. |
Gorr et al., “Crime Hot Spot Forecasting: Modeling and Comparative Evaluation”, Grant 98-IJ-CX-K005, May 6, 2002, 37 pages. |
Goswami, Gautam, “Quite Writly Said!,” One Brick at a Time, Aug. 21, 2005, pp. 7. |
Griffith, Daniel A., “A Generalized Huff Model,” Geographical Analysis, Apr. 1982, vol. 14, No. 2, pp. 135-144. |
Hansen et al., “Analyzing Social Media Networks with NodeXL: Insights from a Connected World”, Chapter 4, pp. 53-67 and Chapter 10, pp. 143-164, published Sep. 2010. |
Haralick et al., “Image Analysis Using Mathematical Morphology,” Pattern Analysis and Machine Intelligence, IEEE Transactions, Jul. 1987, vol. PAMI-9, No. 4, pp. 532-550. |
Hardesty, “Privacy Challenges: Analysis: It's Surprisingly Easy to Identify Individuals from Credit-Card Metadata,” MIT News On Campus and Around the World, MIT News Office, Jan. 29, 2015, 3 pages. |
Hibbert et al., “Prediction of Shopping Behavior Using a Huff Model Within a GIS Framework,” Healthy Eating in Context, Mar. 18, 2011, pp. 16. |
Hogue et al., “Thresher: Automating the Unwrapping of Semantic Content from the World Wide Web,” 14th International Conference on World Wide Web, WWW 2005: Chiba, Japan, May 10-14, 2005, pp. 86-95. |
Huff et al., “Calibrating the Huff Model Using ArcGIS Business Analyst,” ESRI, Sep. 2008, pp. 33. |
Huff, David L., “Parameter Estimation in the Huff Model,” ESRI, ArcUser, Oct.-Dec. 2003, pp. 34-36. |
“HunchLab: Heat Map and Kernel Density Calculation for Crime Analysis,” Azavea Journal, printed from www.azavea.com/blogs/newsletter/v4i4/kernel-density-capabilities-added-to-hunchlab/ on Sep. 9, 2014, 2 pages. |
Ipbucker, C., “Inverse Transformation for Several Pseudo-cylindrical Map Projections Using Jacobian Matrix,” ICCSA 2009, Part 1 LNCS 5592, pp. 553-564. |
Kahan et al., “Annotea: an Open RDF Infrastructure for Shared Web Annotations”, Computer Networks, Elsevier Science Publishers B.V., vol. 39, No. 5, dated Aug. 5, 2002, pp. 589-608. |
keylines.com, “An Introduction to KeyLines and Network Visualization,” Mar. 2014, <http://keylines.com/wp-content/uploads/2014/03/KeyLines-White-Paper.pdf> downloaded May 12, 2014 in 8 pages. |
keylines.com, “KeyLines Datasheet,” Mar. 2014, <http://keylines.com/wp-content/uploads/2014/03/KeyLines-datasheet.pdf> downloaded May 12, 2014 in 2 pages. |
keylines.com, “Visualizing Threats: Improved Cyber Security Through Network Visualization,” Apr. 2014, <http://keylines.com/wp-content/uploads/2014/04/Visualizing-Threats1.pdf> downloaded May 12, 2014 in 10 pages. |
Kitts, Paul, “Chapter 14: Genome Assembly and Annotation Process,” The NCBI Handbook, Oct. 2002, pp. 1-21. |
Levine, N., “Crime Mapping and the Crimestat Program,” Geographical Analysis, 2006, vol. 38, pp. 41-56. |
Li et al., “Interactive Multimodal Visual Search on Mobile Device,” IEEE Transactions on Multimedia, vol. 15, No. 3, Apr. 1, 2013, pp. 594-607. |
Liu, Tianshun, “Combining GIS and the Huff Model to Analyze Suitable Locations for a New Asian Supermarket in the Minneapolis and St. Paul, Minnesota USA,” Papers in Resource Analysis, 2012, vol. 14, pp. 8. |
Madden, Tom, “Chapter 16: The BLAST Sequence Analysis Tool,” The NCBI Handbook, Oct. 2002, pp. 1-15. |
Mandagere, Nagapramod, “Buffer Operations in GIS,” <http://www-users.cs.umn.edu/˜npramod/enc_pdf.pdf> retrieved Jan. 28, 2010, pp. 7. |
Manno et al., “Introducing Collaboration in Single-user Applications through the Centralized Control Architecture,” 2010, pp. 10. |
Manske, “File Saving Dialogs,” <http://www.mozilla.org/editor/ui_specs/FileSaveDialogs.html>, Jan. 20, 1999, pp. 7. |
Map Builder, “Rapid Mashup Development Tool for Google and Yahoo Maps!” <http://web.archive.org/web/20090626224734/http://www.mapbuilder.net/> printed Jul. 20, 2012 in 2 pages. |
Map of San Jose, CA. Retrieved Oct. 2, 2013 from http://maps.yahoo.com. |
Map of San Jose, CA. Retrieved Oct. 2, 2013 from http://maps.bing.com. |
Map of San Jose, CA. Retrieved Oct. 2, 2013 from http://maps.google.com. |
Microsoft—Developer Network, “Getting Started with VBA in Word 2010,” Apr. 2010, <http://msdn.microsoft.com/en-us/library/ff604039%28v=office.14%29.aspx> as printed Apr. 4, 2014 in 17 pages. |
Microsoft Office—Visio, “About connecting shapes,” <http://office.microsoft.com/en-us/visio-help/about-connecting-shapes-HP085050369.aspx> printed Aug. 4, 2011 in 6 pages. |
Microsoft Office—Visio, “Add and glue connectors with the Connector tool,” <http://office.microsoft.com/en-us/visio-help/add-and-glue-connectors-with-the-connector-tool-HA010048532.aspx?CTT=1> printed Aug. 4, 2011 in 1 page. |
Mizrachi, Ilene, “Chapter 1: GenBank: The Nuckeotide Sequence Database,” The NCBI Handbook, Oct. 2002, pp. 1-14. |
Murray, C., Oracle Spatial Developer's Guide—6 Coordinate Systems (Spatial Reference Systems), <http://docs.oracle.com/cd/B28359_01/appdev.111/b28400.pdf>, Jun. 2009. |
Nierman, “Evaluating Structural Similarity in XML Documents”, 6 pages, 2002. |
Olanoff, Drew, “Deep Dive with the New Google Maps for Desktop with Google Earth Integration, It's More than Just a Utility,” May 15, 2013, pp. 1-6, retrieved from the internet: http://web.archive.org/web/20130515230641/http://techcrunch.com/2013/05/15/deep-dive-with-the-new-google-maps-for-desktop-with-google-earth-integration-its-more-than-just-a-utility/. |
Open Street Map, “Amm's Diary:Unconnected ways and other data quality issues,” http://www.openstreetmap.org/user/amm/diary printed Jul. 23, 2012 in 3 pages. |
Palmas et al., “An Edge-Bunding Layout for Interactive Parallel Coordinates” 2014 IEEE Pacific Visualization Symposium, pp. 57-64. |
POI Editor, “How To: Create Your Own Points of Interest,” <http://www.poieditor.com/articles/how_to__create_your_own_points_of_interest/> printed Jul. 22, 2012 in 4 pages. |
“Potential Money Laundering Warning Signs,” snapshot taken 2003, https://web.archive.org/web/20030816090055/http:/finsolinc.com/ANTI-MONEY%20LAUNDERING%20TRAINING%20GUIDES.pdf. |
Pozzi et al., “Vegetation and Population Density in Urban and Suburban Areas in the U.S.A.” Third International Symposium of Remote Sensing of Urban Areas Istanbul, Turkey, Jun. 2002, pp. 8. |
Qiu, Fang, “3d Analysis and Surface Modeling”, <http://web.archive.org/web/20091202221925/http://www.utsa.edu/Irsg/Teaching/EES6513/08-3D.pdf> printed Sep. 16, 2013 in 26 pages. |
Reddy et al., “Under the hood of GeoVRML 1.0,” SRI International, Proceedings of the fifth symposium on Vurtual Reality Modeling Language (Web3D-VRML), New York, NY, Feb. 2000, pp. 23-28. <http://pdf.aminer.org/000/648/038/under_the_hood_of_geovrml.pdf>. |
“Refresh CSS Ellipsis When Resizing Container—Stack Overflow,” Jul. 31, 2013, retrieved from internet http://stackoverflow.com/questions/17964681/refresh-css-ellipsis-when-resizing-container, retrieved on May 18, 2015. |
Reibel et al., “Areal Interpolation of Population Counts Using Pre-classi_ed Land Cover Data,” Population Research and Policy Review, 2007, vol. 26, pp. 619-633. |
Reibel, M., “Geographic Information Systems and Spatial Data Processing in Demography: a Review,” Population Research and Policy Review, 2007, vol. 26, pp. 601-618. |
Rizzardi et al., “Interfacing U.S. Census Map Files with Statistical Graphics Software: Application and Use in Epidemiology,” Statistics in Medicine, Oct. 1993, vol. 12, No. 19-20, pp. 1953-1964. |
Rouse, Margaret, “OLAP Cube,” <http://searchdatamanagement.techtarget.com/definition/OLAP-cube>, Apr. 28, 2012, pp. 16. |
Sigrist, et al., “PROSITE, a Protein Domain Database for Functional Characterization and Annotation,” Nucleic Acids Research, 2010, vol. 38, pp. D161-D166. |
Sirotkin et al., “Chapter 13: The Processing of Biological Sequence Data at NCBI,” The NCBI Handbook, Oct. 2002, pp. 1-11. |
Snyder, “Map Projections—A Working Manual,” U.S. Geological Survey Professional paper 1395, United States Government Printing Office, Washington: 1987, pp. 11-21 and 60-70. |
Sonris, “Using the Area of Interest Tools,” <http://web.archive.org/web/20061001053327/http://sonris-www.dnr.state.la.us/gis/instruct_files/tutslide12> printed Jan. 3, 2013 in 1 page. |
Tangelder et al., “Freeform Shape Matching Using Minkowski Operations,” The Netherlands, Jun. 1996, pp. 12. |
Thompson, Mick, “Getting Started with GEO,” Getting Started with GEO, Jul. 26, 2011. |
Umagandhi et al., “Search Query Recommendations Using Hybrid User Profile with Query Logs,” International Journal of Computer Applications, vol. 80, No. 10, Oct. 1, 2013, pp. 7-18. |
Valentini et al., “Ensembles of Learning Machines”, M. Marinaro and R. Tagliaferri (Eds.): WIRN VIETRI 2002, LNCS 2486, pp. 3-20. |
VB Forums, “Buffer a Polygon,” Internet Citation, <http://www.vbforums.com/showthread.php?198436-Buffer-a-Polygon>, Specifically Thread #1, #5 & #11 retrieved on May 2, 2013, pp. 8. |
Vivid Solutions, “JTS Topology Suite: Technical Specifications,” <http://www.vividsolutions.com/jts/bin/JTS%20Technical%20Specs.pdf> Version 1.4, 2003, pp. 36. |
Wikipedia, “Douglas_Peucker-Algorithms,” <http://de.wikipedia.org/w/index.php?title=Douglas-Peucker-Algorithmus&oldid=91846042> printed Jul. 2011, pp. 2. |
Wikipedia, “Federated Database System,” Sep. 7, 2013, retrieved from the internet on Jan. 27, 2015 http://en.wikipedia.org/w/index.php?title=Federated_database_system&oldid=571954221. |
Wikipedia, “Ramer_Douglas_Peucker_Algorithm,” <http://en.wikipedia.org/wiki/Ramer%E2%80%93Douglas%E2%80%93Peucker_algorithm> printed Jul. 2011, pp. 3. |
Wongsuphasawat et al., “Visual Analytics for Transportation Incident Data Sets,” Transportation Research Record 2138, 2009, pp. 135-145. |
Woodbridge, Stephen, “[geos-devel] Polygon simplification,” <http://lists.osgeo.org/pipermail/geos-devel/2011-May/005210.html> dated May 8, 2011, pp. 3. |
Yang et al., “HTML Page Analysis Based on Visual Cues”, A129, pp. 859-864, 2001. |
International Search Report and Written Opinion in Application No. PCT/US2009/056703, dated Mar. 15, 2010. |
Notice of Allowance for U.S. Appl. No. 13/948,859 dated Dec. 10, 2014. |
Notice of Allowance for U.S. Appl. No. 14/102,394 dated Aug. 25, 2014. |
Notice of Allowance for U.S. Appl. No. 14/108,187 dated Aug. 29, 2014. |
Notice of Allowance for U.S. Appl. No. 14/135,289 dated Oct. 14, 2014. |
Notice of Allowance for U.S. Appl. No. 14/192,767 dated Dec. 16, 2014. |
Notice of Allowance for U.S. Appl. No. 14/225,084 dated May 4, 2015. |
Notice of Allowance for U.S. Appl. No. 14/268,964 dated Dec. 3, 2014. |
Notice of Allowance for U.S. Appl. No. 14/294,098 dated Dec. 29, 2014. |
Notice of Allowance for U.S. Appl. No. 14/319,765 dated Nov. 25, 2016. |
Notice of Allowance for U.S. Appl. No. 14/473,552 dated Jul. 24, 2015. |
Notice of Allowance for U.S. Appl. No. 14/473,860 dated Jan. 5, 2015. |
Notice of Allowance for U.S. Appl. No. 14/486,991 dated May 1, 2015. |
Notice of Allowance for U.S. Appl. No. 14/504,103 dated May 18, 2015. |
Notice of Allowance for U.S. Appl. No. 14/616,080 dated Apr. 2, 2015. |
Official Communication for Australian Patent Application No. 2010227081 dated Mar. 18, 2011. |
Official Communication for Australian Patent Application No. 2010257305 dated Apr. 12, 2011. |
Official Communication for Australian Patent Application No. 2010257305 dated Sep. 22, 2011. |
Official Communication for Australian Patent Application No. 2014201511 dated Feb. 27, 2015. |
Official Communication for Australian Patent Application No. 2014202442 dated Mar. 19, 2015. |
Official Communication for Australian Patent Application No. 2014210604 dated Jun. 5, 2015. |
Official Communication for Australian Patent Application No. 2014210614 dated Jun. 5, 2015. |
Official Communication for Australian Patent Application No. 2014213553 dated May 7, 2015. |
Official Communication for Australian Patent Application No. 2014250678 dated Jun. 17, 2015. |
Official Communication for European Patent Application No. 08839003.4 dated Jun. 12, 2013. |
Official Communication for European Patent Application No. 08839003.4 dated Aug. 14, 2012. |
Official Communication for European Patent Application No. 10195798.3 dated May 17, 2011. |
Official Communication for European Patent Application No. 12186236.1 dated May 17, 2013. |
Official Communication for European Patent Application No. 14158861.6 dated Jun. 16, 2014. |
Official Communication for European Patent Application No. 14159464.8 dated Jul. 31, 2014. |
Official Communication for European Patent Application No. 14180142.3 dated Feb. 6, 2015. |
Official Communication for European Patent Application No. 14180281.9 dated Jan. 26, 2015. |
Official Communication for European Patent Application No. 14180321.3 dated Apr. 17, 2015. |
Official Communication for European Patent Application No. 14180432.8 dated Jun. 23, 2015. |
Official Communication for European Patent Application No. 14186225.0 dated Feb. 13, 2015. |
Official Communication for European Patent Application No. 14187739.9 dated Jul. 6, 2015. |
Official Communication for European Patent Application No. 14187996.5 dated Feb. 12, 2015. |
Official Communication for European Patent Application No. 14189344.6 dated Feb. 20, 2015. |
Official Communication for European Patent Application No. 14189347.9 dated Oct. 13, 2017. |
Official Communication for European Patent Application No. 14189347.9 dated Mar. 4, 2015. |
Official Communication for European Patent Application No. 14189802.3 dated May 11, 2015. |
Official Communication for European Patent Application No. 14191540.5 dated May 27, 2015. |
Official Communication for European Patent Application No. 14197879.1 dated Apr. 28, 2015. |
Official Communication for European Patent Application No. 14197895.7 dated Apr. 28, 2015. |
Official Communication for European Patent Application No. 14199182.8 dated Mar. 13, 2015. |
Official Communication for European Patent Application No. 14189347.9 dated Jun. 8, 2018. |
Official Communication for Great Britain Patent Application No. 1319225.7 dated May 2, 2014. |
Official Communication for Great Britain Patent Application No. 1404457.2 dated Aug. 14, 2014. |
Official Communication for Great Britain Patent Application No. 1404574.4 dated Dec. 18, 2014. |
Official Communication for Great Britain Patent Application No. 1408025.3 dated Nov. 6, 2014. |
Official Communication for Great Britain Patent Application No. 1411984.6 dated Dec. 22, 2014. |
Official Communication for Great Britain Patent Application No. 1413935.6 dated Jan. 27, 2015. |
Official Communication for Netherlands Patent Application No. 2013306 dated Apr. 24, 2015. |
Official Communication for New Zealand Patent Application No. 616167 dated Oct. 10, 2013. |
Official Communication for New Zealand Patent Application No. 622513 dated Apr. 3, 2014. |
Official Communication for New Zealand Patent Application No. 622517 dated Apr. 3, 2014. |
Official Communication for New Zealand Patent Application No. 624557 dated May 14, 2014. |
Official Communication for New Zealand Patent Application No. 627962 dated Aug. 5, 2014. |
Official Communication for New Zealand Patent Application No. 628161 dated Aug. 25, 2014. |
Official Communication for New Zealand Patent Application No. 628263 dated Aug. 12, 2014. |
Official Communication for New Zealand Patent Application No. 628495 dated Aug. 19, 2014. |
Official Communication for New Zealand Patent Application No. 628585 dated Aug. 26, 2014. |
Official Communication for New Zealand Patent Application No. 628840 dated Aug. 28, 2014. |
Official Communication for U.S. Appl. No. 12/556,318 dated Jul. 2, 2015. |
Official Communication for U.S. Appl. No. 12/840,673 dated Sep. 17, 2014. |
Official Communication for U.S. Appl. No. 12/840,673 dated Jan. 2, 2015. |
Official Communication for U.S. Appl. No. 13/247,987 dated Apr. 2, 2015. |
Official Communication for U.S. Appl. No. 13/728,879 dated Mar. 17, 2015. |
Official Communication for U.S. Appl. No. 13/728,879 dated Jan. 27, 2015. |
Official Communication for U.S. Appl. No. 13/831,791 dated Mar. 4, 2015. |
Official Communication for U.S. Appl. No. 13/835,688 dated Jun. 17, 2015. |
Official Communication for U.S. Appl. No. 13/839,026 dated Aug. 4, 2015. |
Official Communication for U.S. Appl. No. 14/148,568 dated Oct. 22, 2014. |
Official Communication for U.S. Appl. No. 14/148,568 dated Mar. 26, 2015. |
Official Communication for U.S. Appl. No. 14/196,814 dated May 5, 2015. |
Official Communication for U.S. Appl. No. 14/225,006 dated Sep. 10, 2014. |
Official Communication for U.S. Appl. No. 14/225,006 dated Feb. 27, 2015. |
Official Communication for U.S. Appl. No. 14/225,084 dated Sep. 2, 2014. |
Official Communication for U.S. Appl. No. 14/225,084 dated Feb. 20, 2015. |
Official Communication for U.S. Appl. No. 14/225,160 dated Feb. 11, 2015. |
Official Communication for U.S. Appl. No. 14/225,160 dated Aug. 12, 2015. |
Official Communication for U.S. Appl. No. 14/225,160 dated May 20, 2015. |
Official Communication for U.S. Appl. No. 14/225,160 dated Oct. 22, 2014. |
Official Communication for U.S. Appl. No. 14/225,160 dated Jul. 29, 2014. |
Official Communication for U.S. Appl. No. 14/268,964 dated Sep. 3, 2014. |
Official Communication for U.S. Appl. No. 14/289,596 dated Jul. 18, 2014. |
Official Communication for U.S. Appl. No. 14/289,596 dated Jan. 26, 2015. |
Official Communication for U.S. Appl. No. 14/289,596 dated Apr. 30, 2015. |
Official Communication for U.S. Appl. No. 14/289,599 dated Jul. 22, 2014. |
Official Communication for U.S. Appl. No. 14/289,599 dated May 29, 2015. |
Official Communication for U.S. Appl. No. 14/294,098 dated Aug. 15, 2014. |
Official Communication for U.S. Appl. No. 14/294,098 dated Nov. 6, 2014. |
Official Communication for U.S. Appl. No. 14/306,138 dated Feb. 18, 2015. |
Official Communication for U.S. Appl. No. 14/306,138 dated Sep. 23, 2014. |
Official Communication for U.S. Appl. No. 14/306,138 dated May 26, 2015. |
Official Communication for U.S. Appl. No. 14/306,147 dated Feb. 19, 2015. |
Official Communication for U.S. Appl. No. 14/306,147 dated Aug. 7, 2015. |
Official Communication for U.S. Appl. No. 14/306,147 dated Sep. 9, 2014. |
Official Communication for U.S. Appl. No. 14/306,154 dated Mar. 11, 2015. |
Official Communication for U.S. Appl. No. 14/306,154 dated May 15, 2015. |
Official Communication for U.S. Appl. No. 14/306,154 dated Jul. 6, 2015. |
Official Communication for U.S. Appl. No. 14/306,154 dated Sep. 9, 2014. |
Official Communication for U.S. Appl. No. 14/319,161 dated Jan. 23, 2015. |
Official Communication for U.S. Appl. No. 14/319,765 dated Jun. 16, 2015. |
Official Communication for U.S. Appl. No. 14/319,765 dated Nov. 25, 2014. |
Official Communication for U.S. Appl. No. 14/319,765 dated Feb. 4, 2015. |
Official Communication for U.S. Appl. No. 14/323,935 dated Jun. 22, 2015. |
Official Communication for U.S. Appl. No. 14/323,935 dated Nov. 28, 2014. |
Official Communication for U.S. Appl. No. 14/323,935 dated Mar. 31, 2015. |
Official Communication for U.S. Appl. No. 14/326,738 dated Dec. 2, 2014. |
Official Communication for U.S. Appl. No. 14/326,738 dated Jul. 31, 2015. |
Official Communication for U.S. Appl. No. 14/326,738 dated Mar. 31, 2015. |
Official Communication for U.S. Appl. No. 14/473,552 dated Feb. 24, 2015. |
Official Communication for U.S. Appl. No. 14/486,991 dated Mar. 10, 2015. |
Official Communication for U.S. Appl. No. 14/504,103 dated Mar. 31, 2015. |
Official Communication for U.S. Appl. No. 14/504,103 dated Feb. 5, 2015. |
Official Communication for U.S. Appl. No. 14/579,752 dated Aug. 19, 2015. |
Official Communication for U.S. Appl. No. 14/579,752 dated May 26, 2015. |
Official Communication for U.S. Appl. No. 14/639,606 dated May 18, 2015. |
Official Communication for U.S. Appl. No. 14/639,606 dated Jul. 24, 2015. |
Official Communication for U.S. Appl. No. 14/672,009 dated Jul. 14, 2017. |
Official Communication for U.S. Appl. No. 14/672,009 dated May 26, 2017. |
Official Communication for U.S. Appl. No. 14/672,009 dated Jan. 9, 2018. |
Notice of Allowance for U.S. Appl. No. 14/581,823 dated Apr. 6, 2018. |
Official Communication for U.S. Appl. No. 14/581,823 dated Sep. 1, 2017. |
Official Communication for U.S. Appl. No. 14/581,823 dated Nov. 2, 2017. |
Coplink, “Incident Analyzer User Guide,” created Nov. 5, 2010 (as indicated by the PDF file metadata), 14 pages. |
Gatewaynews, “New Crime Fighting Tool ‘Coplink’” available at https://www.youtube.com/watch?v=GbU6E0grnTw, as published on Mar. 8, 2008. |
I2—An IBM Company, “IBM i2 Intelligent Law Enforcement Demo,” available at https://www.youtube.com/watch?v=_KCXZ2iTMXQ, as published on Dec. 3, 2012. |
I2 A ChoicePoint Company, “i2 Analyst's Notebook 7 User Guide: Creating Charts” Jun. 2007, 373 pages. |
IBM—Data analysis—i2 Analyst's Notebook, http://www-03.ibm.com/software/products/en/analysts-notebook, as printed Feb. 16, 2017 in 2 pages. |
IBM—i2 Analyze, https://www-03.ibm.com/software/products/en/i2-analyze, as printed Feb. 15, 2017 in 2 pages. |
IBM—i2 Integrated Law Enforcement, https://www-03.ibm.com/software/products/en/integrated-law-enforcement, as printed Feb. 15, 2017 in 2 pages. |
IBM Analytics, “IBM i2 Intelligence Analysis Portfolio Overview,” available at https://www.youtube.com/watch?v=EIFu_oUiaBY, as published on Sep. 24, 2015. |
IBM Corporation, “IBM i2 Analyst's Notebook Connector for Esri,” May 2012, in 3 pages. |
IBM Corporation, “IBM i2 Analyst's Notebook,” Aug. 2015, in 4 pages. |
IBM Corporation, “IBM i2 Enterprise Insight Analysis V2.0 delivers a modern contextual user interface and enhanced software operational warehouse support,” http://www-01.ibm.com/common/ssi/ShowDoc.wss?docURL=/common/ssi/rep_ca/2/897/ENUS215-302/index.html&lang=en&request_locale=en, as published on Sep. 1, 2015. |
IBM Support, “Software lifecycle—i2 Analyst's Notebook Premium 9.0.0,” https://www-01.ibm.com/software/support/lifecycleapp/PLCDetail.wss?q45=I570331B72886X86, as printed Mar. 7, 2017 in 1 page. |
IBM Support, “Software lifecycle—i2 Enterprise Insight Analysis 2.0.0,” https://www-01.ibm.com/software/support/lifecycleapp/PLCDetail.wss?q45=E170786H45496I53, as printed Mar. 7, 2017 in 1 page. |
Visual Analysis, “Overview of importing data and creating timelines,” available at https://www.youtube.com/watch?v=SovxKrvkZZs, as published on Mar. 9, 2015. |
Visual Analysis, “Overview of merging timeline charts and creating hybrid charts,” available at https://www.youtube.com/watch?v=dl6jzNtEVpA, as published on Mar. 9, 2015. |
Yair Shaked, “IBM i2 Enterprise Insight Analysis—cyber Demo,” available at https://www.youtube.com/watch?v=ZXmTWKqkfF4, as published on Nov. 19, 2015. |
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Child | 14581823 | US |