Patent Grant
8856182
The invention relates generally to database reporting and particularly to user access and configuration of databases.
Contact centers, such as Automatic Call Distribution or ACD systems, are employed by many enterprises to service customer contacts. A typical contact center includes a switch and/or server to receive and route incoming packet-switched and/or circuit-switched contacts and one or more resources, such as human agents and automated resources (e.g., Interactive Voice Response (IVR) units), to service the incoming contacts. Contact centers distribute contacts, whether inbound or outbound, for servicing to any suitable resource according to predefined criteria. In many existing systems, the criteria for servicing the contact from the moment that the contact center becomes aware of the contact until the contact is connected to an agent are customer-specifiable (i.e., programmable by the operator of the contact center), via a capability called vectoring. Normally in present-day ACDs when the ACD system's controller detects that an agent has become available to handle a contact, the controller identifies all predefined contact-handling skills of the agent (usually in some order of priority) and delivers to the agent the highest-priority oldest contact that matches the agent's highest-priority skill.
The primary objective of contact center management, including call-distribution algorithms, is to ultimately maximize contact center performance and profitability. An ongoing challenge in contact center administration is monitoring of selected data entities associated with contact center operation to optimize the use of contact center resources and maximize agent performance and profitably. Current products for monitoring and reporting on contact center performance, such as Call Management System or CMS™ and Avaya IQ™ by Avaya, Inc., are configured as data warehouses that extract data from multiple sources, transform the data into a normalized form, and load the data into the data warehouse database, typically on a real time basis.
A common type of data warehouse is based on dimensional modeling. Dimensional modeling is a data model that divides the world into measurements and context. Measurements are usually numeric and taken repeatedly. Numeric measurements are facts. Facts are surrounded by textual context in existence when the fact is recorded. Context is often subdivided into dimensions. Fact tables are used in dimensional modeling to logically model measurements with multiple foreign keys referring to the contextual entities. The contextual entities each have an associated primary key. A “key” is a data element (e.g., attribute or column) that identifies an instance of an entity or record in a collection of data, such as a table. A “primary key” is a column or combination of columns whose values uniquely identify a row in a table or is the attribute or group of attributes selected from the candidate keys as the most suitable to uniquely identify each instance of an entity. A “foreign key” refers to a column or combination of columns whose values are required to match a primary key in another table or is a primary key of a parent entity that contributes to a child entity across a relationship. Types of primary keys include a natural key, or a key having a meaning to users, and a surrogate key, or a key that is artificially or synthetically established, meaningless to users, and used as a substitute for a natural key.
If the same entity (e.g., agent) is represented on multiple data sources (e.g., inbound call system and outbound call system) by different natural keys, a traditional data warehouse generates and assigns a surrogate key to identify the entity. The surrogate key is an internal identifier managed by the data warehouse. For example, in a contact center an agent may handle inbound calls from one system and outbound calls from another system, with different identities on each system. Data warehouses commonly process each data source independently, performing data correlation across sources at a later time.
Some data models specify a behavior known as a type 2 slowly changing dimension. A type 2 dimension tracks the history of changes to an entity over time. When an attribute of an entity is changed, such as when a contact center agent changes their skill set or group membership, a new surrogate key for that entity is generated, and a new row inserted into the database. Fact data associated with the entity can now be tracked separately for activities that occurred before versus after the change by referencing the appropriate surrogate key.
Business intelligence software, such as sold under the tradename COGNOS 8 provided by Cognos, is an example of a data warehouse. Using web-based tools, e.g. Cognos “Report Studio”, business intelligence software can provide “drag and drop” report creation based on selected data stored in a database. This technology relies on proprietary query engines to construct appropriate Structure Query Language (SQL) queries based on descriptive information in a “metadata model” created e.g. through the Cognos “Framework Manager” tool. Instead of mere schema definition, the metadata model defines all the transformations and business rules needed to cook the raw data into the final report metrics.
Business intelligence software is used in Avaya IQ™, which is an example of a data warehouse tailored for contact center data collection and reporting. Avaya IQ™ has a number of differing layers or components. A first component, referred to as “Tables”, is the database fact and dimension tables containing the collected data. A second component, referred to as “Views”, is a set of database views to enable access to the data in the Tables. A third component, referred to herein as “Reporting Model”, provides a schema definition and defines the transformations and business rules needed to convert the data into the final reports. This third component is also referred to in COGNOS 8 as the aforementioned metadata model. A fourth component, referred to as “Reports”, provides report specifications for the final reports.
Business intelligence software generally provides only limited database dependency information to an unsophisticated user. In COGNOS 8, for example, one performs forward tracing, from a given object to other objects that reference it in their defining expressions, using a feature “Find Report Dependencies”. This feature allows the user to select any object (or collection of objects) in the reporting model and find the list of reports that depend on the object. But the definition of “depend” is limited to those reports that explicitly and directly reference the object in question, so it provides the correct answer only for those few objects that include the thin interface layer (presentation layer) of the reporting model. It does not reveal indirect (chained) dependencies at all. Attempting to use this feature on the vast majority of internal objects in the reporting model (including those at the lowest layer corresponding to items in the database) can give a false impression that no reports depend upon such objects so those objects can be safely deleted from the model. Even for objects in the interface layer that are used by reports, this feature fails to identify the particular items within the report that reference the object in question. To answer that question, the user must open each individual report using the “Report Studio” tool and check manually the expression for all the data items in all the queries defined for that report. Furthermore, the “Find Report Dependencies” feature does not address dependencies between pairs of objects within the reporting model. The only way, that the reporting model user can determine if and where an object is used elsewhere in the model, is to delete that object and hope to see a warning message listing the dependent objects. But even this technique gives occasional false assurances (in cases involving query items in an object known as a query subject shortcut). There is also another feature, “Analyze Publish Impact”, that allows the author of the reporting model to determine which reports will be affected by an, as yet, unpublished change to the reporting model. This was the precursor feature to “Find Report Dependencies” and suffers from the save short falls, plus the added disadvantage that it requires the user to modify the reporting model to see any results.
Backward tracing, from a given object to the other objects that are referenced in its defining expression, would seem to be straight forward, but it is not. The normal operation of Framework Manager allows a user to select an object from a deeply branched tree of previously defined objects and include its reference as a term in the expression for a new/modified object. Nominally, all the user must do to trace backward to those included objects is examine the saved expression and check for references to any predecessor objects. The problem in the reporting model environment is that object references include only the nearest namespace object without identifying where in the deeply branched tree that namespace is located. There is no index of namespaces that can lead one back to a particular namespace and examine the objects it contains. The user must simply know the overall structure of the deeply branched tree (containing hundreds of namespaces) and do an exhaustive manual search of each tree branch until the desired namespace is found. For the broader problem of tracing from a particular item in a particular report backward to the database, the user must start by opening that report in the Report Studio tool and examining the expression for the item in the report query. Not only is this a time-consuming manual operation but also it simply leads back to the reporting model and the problem described above with reference to the Framework Manager tool. To trace backward to the raw database side of the reporting model, the user must have the author's knowledge of the reporting model structure.
With respect to tracing indirect dependencies based on foreign keys of filters, the Framework Manager tool does define and diagram relationships between objects (similar to foreign key relationships between database tables), but their use is limited to the heuristic rules embedded in the proprietary query engine software that generates actual Structured Query Language (SQL) queries from particular report specifications. Following such relationships is important to identifying which foreign key column in a database fact table determines the choice of rows displayed from a dimension table. Highly skilled authors of reporting models have sufficient sophistication to second guess how the query engine is likely to infer such indirect dependencies, but the tools do not reveal how specific indirect dependencies are established. Part of the difficulty is that this determination cannot be made from the reporting model alone. It requires the context of a particular query from a particular report to estimate how such dependencies are established. The Report Studio feature allows the user to examine a prototype of the SQL code that would be generated on behalf of a particular report query. Such queries may contain hundreds of lines of SQL code that only a database expert with great patience could decipher to trace indirect dependencies. This is not a practical way for tracing indirect dependencies.
There remains a need for quality, clarity, verifiability, and maintainability. Reporting models can be enormous and complex in comparison to the data model. In view of the complexity, the reports can be worthless if the data they produce cannot be understood and trusted. Pertinent questions to be understood include: (i) what report values, if any, derive from a particular item in the database (e.g., in case the database is in error or to know how it is manifested for testing); (ii) what database items contribute to a particular value in a report (e.g., to isolate the problem in case the report value is in error); (iii) how does a particular report item derive from database values and what is the formula (e.g., to document the report verify the business rules or instill customer confidence); (iv) even if a particular database item is not in an existing report, is it available for inclusion in future reports (e.g., are reportability and customization requirements met); and (v) when a reporting model is being used, how does an object in the reporting model trace forward toward reports or back toward the database (e.g., is this object needed). In short, database reporting applications require transparency and traceability in both directions between the database and the reports. It is therefore desirable to provide an interface permitting users of a wide variety of differing levels of technical expertise to understand what data is produced for reporting and how that data relates back to the raw data in the database.
Microsoft Access 2007 provides relevant features, but outside of the business intelligence arena. This product provides a feature, known as “Object Dependencies pane”, which allows the user to see both “Objects that depend on me” and “Objects that I depend on”. It can determine what report values, if any, derive from a particular item in the database and what database items contribute to a particular value in a report but the approach is limited in the depth of dependencies that can be displayed and is specific to the Microsoft Access environment where reports and databases are part of the same proprietary package. It therefore does not address the current problems in the business intelligence domain due to its narrow focus and scaling limitations (e.g., it is unable to do end-to-end dependencies for large or complex systems due to depth limitations).
These and other needs are addressed by the various embodiments and configurations of the present invention. The invention is directed generally to a database warehouse tool to assist user interaction with dependencies among the reporting objects and the database.
In one embodiment, a database system includes a database defined by a data model, a metadata model comprising descriptive information, the descriptive information defining transformations and rules to convert raw data in the database to selected output, and a query engine to construct, based on user input and the descriptive information, appropriate queries and/or commands to the database. The data and metadata models collectively define a hierarchical tree structure. A tool is provided to assist the user in interacting with the query model by displaying a plurality of linked images to the user. The images enable the user to perform one or more of the following steps:
(B1) forward tracing from a selected first item in a first level of the graph to a second item in a second level of the graph, the second item depending upon the first item, by selecting a second link in a first image, the second link being associated with the second item and, in response, providing the user with a second image containing, in turn, the definition and/or dependency information respecting the second item;
In one configuration of step (B3), a web page presents the expression with each term hyperlinked back to the object being referenced. Back tracing does not require a manual hunt among the many branches of a deeply nested reporting model tree to find an object mentioned as a term in a defining expression. In addition, the full context of the current object is listed at the top of the window to provide the hierarchical location within the tree and allow intermediate navigation to its intermediate nodes.
In one configuration of step (B5), related foreign keys are listed in a web page associated with a selected item.
In one configuration of step (B6), related locale filters are listed in a web page associated with a selected item.
In one configuration of step (B7), end-to-end forward and backward dependencies are listed in a data base report cross reference spreadsheet showing each report item that ultimately depends upon any particular database column and any database column that ultimately contributes to any particular report value. Dependencies are also traceable to individual data items within individual queries of the report, not just to the overall report. Furthermore, multiple degrees of report usage are provided so that accurate usage can be determined even for objects throughout the reporting model, not just those objects in the thin outermost interface layer of the reporting model.
As can be seen, the embodiment can combine new methods for deducing report-database dependencies with the recognition that reporting models are better described as webs rather than trees to produce web pages and spreadsheets generated automatically from existing business intelligence metadata that make accurate report content and dependency information available to a wide audience, in contrast to the incomplete and inaccurate information previously available only to highly skilled practitioners of the art.
The present invention can provide a number of advantages depending on the particular configuration. For example, the tool can permit users of wide levels of technical sophistication to interact efficiently and effectively with even complex databases and reporting architectures. The use of web sites and spreadsheets to provide the information to the user is a familiar and widely accessible format. Users can access the information readily using a conventional web browser. Users can understand and trust reports generated from the database, thereby providing quality, clarity, verifiability, and maintainability. The tool can permit users to debug, document, and customize reports without adversely impacting the integrity of the underlying data structures. The tool can readily enable forward and back tracing, providing, in layered reporting architectures, transparency and traceability in both directions towards and away from the database. The tracing provides more than simply following explicit referencing of one object by another object. In addition to such static dependencies, indirect dynamic dependencies implied by relations between items can be traced forwards or backwards.
These and other advantages will be apparent from the disclosure of the invention(s) contained herein.
The phrases “plurality”, “at least one”, “one or more”, and “and/or” are open-ended expressions that are both conjunctive and disjunctive in operation. For example, each of the expressions “a plurality of A, B and C”, “at least one of A, B and C”, “at least one of A, B, or C”, “one or more of A, B, and C”, “one or more of A, B, or C” and “A, B, and/or C” means A alone, B alone, C alone, A and B together, A and C together, B and C together, or A, B and C together.
The term “a” or “an” entity refers to one or more of that entity. As such, the terms “a” (or “an”), “one or more” and “at least one” can be used interchangeably herein. It is also to be noted that the terms “comprising”, “including”, and “having” can be used interchangeably.
The term “automatic” and variations thereof, as used herein, refers to any process or operation done without material human input when the process or operation is performed. However, a process or operation can be automatic even if performance of the process or operation uses human input, whether material or immaterial, received before performance of the process or operation. Human input is deemed to be material if such input influences how the process or operation will be performed. Human input that consents to the performance of the process or operation is not deemed to be “material”.
The term “forward tracing” refers to iteratively locating one or more items that depend on a selected item. An example of forward tracing is shown by arrow 320 in
The term “back tracing” refers to iteratively locating one or more items upon which a selected item depends. An example of back tracing is shown by arrow 324 in
The term “computer-readable medium” as used herein refers to any tangible storage and/or transmission medium that participate in providing instructions to a processor for execution. Such a medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media includes, for example, NVRAM, or magnetic or optical disks. Volatile media includes dynamic memory, such as main memory. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, magneto-optical medium, a CD-ROM, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, a solid state medium like a memory card, any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read. A digital file attachment to e-mail or other self-contained information archive or set of archives is considered a distribution medium equivalent to a tangible storage medium. When the computer-readable media is configured as a database, it is to be understood that the database may be any type of database, such as relational, hierarchical, object-oriented, and/or the like. Accordingly, the invention is considered to include a tangible storage medium or distribution medium and prior art-recognized equivalents and successor media, in which the software implementations of the present invention are stored.
The term “data stream” refers to the flow of data from one or more, typically external, upstream sources to one or more downstream reports.
The term “dependency” or “dependent” refers to direct and indirect relationships between items. For example, item A depends on item B if one or more of the following is true: (i) A is defined in terms of B (B is a term in the expression for A); (ii) A is selected by B (B is a foreign key that chooses which A); and (iii) A is filtered by B (B is a term in a filter expression for A). The dependency is “indirect” if (i) is not true; i.e. indirect dependencies are based solely on selection (ii) and or filtering (iii).
The terms “determine”, “calculate” and “compute,” and variations thereof, as used herein, are used interchangeably and include any type of methodology, process, mathematical operation or technique.
The term “item” refers to data fields, such as those defined in reports, reporting model, views, or tables in the database.
The term “module” as used herein refers to any known or later developed hardware, software, firmware, artificial intelligence, fuzzy logic, or combination of hardware and software that is capable of performing the functionality associated with that element. Also, while the invention is described in terms of exemplary embodiments, it should be appreciated that individual aspects of the invention can be separately claimed.
The preceding is a simplified summary of the invention to provide an understanding of some aspects of the invention. This summary is neither an extensive nor exhaustive overview of the invention and its various embodiments. It is intended neither to identify key or critical elements of the invention nor to delineate the scope of the invention but to present selected concepts of the invention in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other embodiments of the invention are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
Although the present invention is discussed with reference to a contact center architecture, it is to be understood that the invention can be applied to numerous other architectures, such as business intelligence applications. The present invention is intended to include these other architectures.
The agent communication devices 100 and incoming contacts from customer communication devices can be assigned to one another using a queue configuration. Each contact queue (not shown) corresponds to a different set of agent skills, as does each agent queue (not shown). Contacts are prioritized and either are enqueued in individual ones of the contact queues in their orders of priority or are enqueued in different ones of a plurality of contact queues that correspond to a different priority. Likewise, each agent's skills are prioritized according to his or her level of expertise in that skill, and either agents are enqueued in individual ones of agent queues in their order of expertise level or are enqueued in different ones of a plurality of agent queues that correspond to a skill and each one of which corresponds to a different expertise level. Contacts incoming to the contact center are assigned to different contact queues based upon a number of predetermined criteria, including customer identity, customer needs, contact center needs, current contact center queue lengths, customer value, and the agent skill that is required for the proper handling of the contact.
The various activities of the agents and their respective communication devices 100, such as ringing and answering, are tracked through events. The events are converted by event processors 112 into agent performance data in a reporting database 116. Data structures maintained in the database 116 are described in more detail in copending U.S. application Ser. No. 10/861,193, filed Jun. 3, 2004, entitled “Data Model of Participation in Multi-Channel and Multi-Party Contacts”, to Kiefhaber, et al., which is fully incorporated herein by this reference. In one configuration, the data structures in the database 116 are defined by a dimensional model, which describes tables and columns in the physical data stores. Examples of data structure attributes describing a customer contact with the contact center include contact identifier, contact type, outbound contact initiation method, customer identifier, data source identifier, party identifier, business role code, party role start timestamp, contact direction code, contact direction description, state identifier, trunk identifier, telephone address, contact participation group, contact part purpose, contact part related reason, contact media type, contact disposition, contact routing method, contact wait treatment, contact qualifier, dialed number purpose, routing construct, and state reason. Other data structures describe attributes of data entities other than contact-related items, such as queues and contact center resources, particularly human agents.
Report servers 120 access the data in the database 116, transform it according to complex rules, and present the resulting reports for viewing by supervisors 124. Embodiments of the present invention can illuminate the complex rules used by the report servers 120.
The table and view layers 200 and 204, respectively, define the interface presented by the database to a reporting model 208. The reporting model 208 (which contains descriptive information defining rules and transformations to convert physical data items into output, such as calculations and performance metrics, query subjects that are accessible to reports) (e.g., historical and real-time reporting models) is where the bulk of the complex data transformation rules are controlled. The source code defining the reporting model is typically maintained in an XML file, while the output of the reporting model is published in various packages (not shown) for use in defining reports. Packages may be saved in XML files or kept in a separate database known as a content store (not shown).
The report layer 212 uses the transformed measures that have been exposed in the published reporting model packages to define report specifications which are also typically saved in XML files or in the content store. When a report user requests a particular report, the report server 120 consults the report specification to construct an appropriate database query, based on the information in the reporting model package. The query is executed by the database and the results are formatted and returned by the report server to the report user.
Construction of the complex rules within the reporting model, and to some extent within the report layer, relies on highly skilled people using specialized tools. A model editing tool 216 is used to construct and modify the reporting model and publish its packages. Similarly a report editing tool 220 is used to construct and modify the report specifications in the report layer.
In a typical commercial business intelligence application, the whole reporting environment, including the report server 120, the reporting model 208, the report layer 212 and the tools 216 and 220 are provided together as suite of products comprising a reporting system. An example of such a system is IBM's Cognos ReportNet, later known as Cognos 8. In that system, the model editing tool 216 is known as Framework Manager, and the report editing tool is either Report Studio or Query Studio. The box labeled Data Stream Reference 224 is provided according to the principles of the present invention.
In one configuration, the reporting model is subdivided into database, data marts, subject areas, data sources, parameter maps, and packages sections. The reporting model is normally organized as a tree hierarchy of namespaces and query subjects, culminating in individual calculations, filters, and query items.
It should be emphasized that the configurations shown in
In one configuration, the data stream reference module 224 analyzes artifacts, along with optional schema specifications of tables and views from the data model, and generates graphical images, such as a static web site, documenting all or part of the data stream, from database to reports, including internals of the reporting model. In one configuration, forward dependencies are displayed and followed by clicking hyperlinks, and backward dependencies by clicking selectable icons in the expressions that define objects. The selectable icons can be, for instance, hyperlinks and right-click menus (hereinafter “links”).
The tree structure of the deeply branched reporting model tree can be navigated by (a) expanding or contracting individual branches to reach the leaves desired, (b) by hopping from one leaf to another (e.g., across branches) by following dependency links, (c) by hopping from a leaf to any of the lower branches to which it belongs, (d) by searching a variety of alphabetical indexes (e.g., by scrolling, jumping to sections, or by using the web browser Find in Page capability), or (e) by using third party web search engines applied to the specific web site.
Textual definitions of individual objects can be displayed, and the module can provide the capability to import and export these definitions into/from eXtended Markup Language (XML) specification of the reporting model. The resulting effect can be analogous to data dictionaries produced by data modeling tools.
In addition to step-by-step following of dependencies, the net effects of dependencies are available in other forms, such as (a) spreadsheets listing all pairings of database columns with dependent report items, (b) single page displays of chained expressions involved in the definition of a single report data item, and (c) at-a-glance tagging of all items in the reporting model. The latter feature distinguishes five degrees of report dependence, the highest being “reported” indicating that the item is referenced directly by at least one report, followed in degrees by “exposed” indicating that no current report references it but that it is available in the external user interface so that reports can include it selected by the user, “required” indicating that it is a lower level item supporting a reported item, “expected” indicating that it is a lower level item supporting an exposed item, and finally “optional” indicating that the item does not contribute in any way to the external interface and can be removed safely without any detrimental effect on the data analysis. Usage can be derived in a way that includes the indirect dynamic dependencies that are only meaningful in the context of a specific report query.
The module can provide both direct and indirect dependency relations. Dependency relations are determined by parsing the various inputs to identify objects and the object they reference. The relationships expressed in the reporting model are also parsed as individual objects, which in turn establish tentative usage dependencies between the objects mentioned in the original relationship object. All such relationship objects involving a particular parent object are collected into another artificial object known as the relationship list. When a report dependency reaches an object that depends on a relationship list, the relationship list is consulted to identify only those child objects (e.g., like foreign key references) that belong to other object collections (query subjects) involved in the current report query. Similarly, query subject filters are also parsed as separate objects and the other objects in that query are declared to depend on the filter object. The module 250 also includes tests to identify and prevent needless repetitions of dependencies. These methods reproduce the expectations of skilled reporting model authors as they understand the implications of the (frequently proprietary) query engines, so that useful dependency results can be derived without knowing the internal details of the query engines.
The presentation methods, which decide how to partition a, commonly large, reporting model into manageably sized images (e.g., web pages) follow the trunk of the tree outward towards the leaves until the branching ratio exceeds a predetermined threshold or until objects of certain determined types are found.
Presentation of the report structures include a method to identify the primary query among the many queries typically found in a particular report. These methods, together with the use of cooperating HyperText Markup Language (HTML) frames, allow the user to navigate through complex models with tens of thousands of objects without having to wait for long pages to download.
The operation of the data stream reference module 224 will be described with reference to
In another back tracing example, the user selects, in the expression for IntervalActiveDur 1202, the item [Facts].[Agent State Sum].[IntervalStateDur.]1208, which generates a further screenshot. In this screenshot, the user selects, in the expression for item 1208, the item [Dimensional Tables].[AgentStateSum].[IntervalStateDur] 328, which provides yet another screenshot, describing, in the expression for [Dimensional Tables].[AgentStateSum].[IntervalStateDur], a database query subject that queries the view [AgentStateSum] (in the view layer 304) that queries a summary fact table in the database.
Selecting the relations in screenshot 1500 yields the screenshot 1600 of
With reference to
Referring again to
The module 224 can provide other forms of dependency information.
With reference to
The exemplary systems and methods of this invention have been described in relation to a data warehouse in a contact center. However, to avoid unnecessarily obscuring the present invention, the preceding description omits a number of known structures and devices. This omission is not to be construed as a limitation of the scope of the claimed invention. Specific details are set forth to provide an understanding of the present invention. It should however be appreciated that the present invention may be practiced in a variety of ways beyond the specific detail set forth herein.
Furthermore, while the exemplary embodiments illustrated herein show the various components of the system collocated, certain components of the system can be located remotely, at distant portions of a distributed network, such as a LAN and/or the Internet, or within a dedicated system. Thus, it should be appreciated, that the components of the system can be combined in to one or more devices, such as a server, or collocated on a particular node of a distributed network, such as an analog and/or digital telecommunications network, a packet-switch network, or a circuit-switched network. It will be appreciated from the preceding description, and for reasons of computational efficiency, that the components of the system can be arranged at any location within a distributed network of components without affecting the operation of the system. For example, the various components can be located in a switch such as a PBX and media server, gateway, in one or more communications devices, at one or more users' premises, or some combination thereof. Similarly, one or more functional portions of the system could be distributed between a telecommunications device(s) and an associated computing device.
Furthermore, it should be appreciated that the various links connecting the elements can be wired or wireless links, or any combination thereof, or any other known or later developed element(s) that is capable of supplying and/or communicating data to and from the connected elements. These wired or wireless links can also be secure links and may be capable of communicating encrypted information. Transmission media used as links, for example, can be any suitable carrier for electrical signals, including coaxial cables, copper wire and fiber optics, and may take the form of acoustic or light waves, such as those generated during radio-wave and infra-red data communications.
Also, while the flowcharts have been discussed and illustrated in relation to a particular sequence of events, it should be appreciated that changes, additions, and omissions to this sequence can occur without materially affecting the operation of the invention.
A number of variations and modifications of the invention can be used. It would be possible to provide for some features of the invention without providing others.
For example in one alternative embodiment, the data stream reference module is applied with other types of data structures, such as object oriented and relational databases.
In another alternative embodiment, the data stream reference module is applied in architectures other than contact centers, such as workflow distribution systems.
In yet another embodiment, the systems and methods of this invention can be implemented in conjunction with a special purpose computer, a programmed microprocessor or microcontroller and peripheral integrated circuit element(s), an ASIC or other integrated circuit, a digital signal processor, a hard-wired electronic or logic circuit such as discrete element circuit, a programmable logic device or gate array such as PLD, PLA, FPGA, PAL, special purpose computer, any comparable means, or the like. In general, any device(s) or means capable of implementing the methodology illustrated herein can be used to implement the various aspects of this invention. Exemplary hardware that can be used for the present invention includes computers, handheld devices, telephones (e.g., cellular, Internet enabled, digital, analog, hybrids, and others), and other hardware known in the art. Some of these devices include processors (e.g., a single or multiple microprocessors), memory, nonvolatile storage, input devices, and output devices. Furthermore, alternative software implementations including, but not limited to, distributed processing or component/object distributed processing, parallel processing, or virtual machine processing can also be constructed to implement the methods described herein.
In yet another embodiment, the disclosed methods may be readily implemented in conjunction with software using object or object-oriented software development environments that provide portable source code that can be used on a variety of computer or workstation platforms. Alternatively, the disclosed system may be implemented partially or fully in hardware using standard logic circuits or VLSI design. Whether software or hardware is used to implement the systems in accordance with this invention is dependent on the speed and/or efficiency requirements of the system, the particular function, and the particular software or hardware systems or microprocessor or microcomputer systems being utilized.
In yet another embodiment, the disclosed methods may be partially implemented in software that can be stored on a storage medium, executed on programmed general-purpose computer with the cooperation of a controller and memory, a special purpose computer, a microprocessor, or the like. In these instances, the systems and methods of this invention can be implemented as program embedded on personal computer such as an applet, JAVA® or CGI script, as a resource residing on a server or computer workstation, as a routine embedded in a dedicated measurement system, system component, or the like. The system can also be implemented by physically incorporating the system and/or method into a software and/or hardware system.
Although the present invention describes components and functions implemented in the embodiments with reference to particular standards and protocols, the invention is not limited to such standards and protocols. Other similar standards and protocols not mentioned herein are in existence and are considered to be included in the present invention. Moreover, the standards and protocols mentioned herein and other similar standards and protocols not mentioned herein are periodically superseded by faster or more effective equivalents having essentially the same functions. Such replacement standards and protocols having the same functions are considered equivalents included in the present invention.
The present invention, in various embodiments, configurations, and aspects, includes components, methods, processes, systems and/or apparatus substantially as depicted and described herein, including various embodiments, subcombinations, and subsets thereof. Those of skill in the art will understand how to make and use the present invention after understanding the present disclosure. The present invention, in various embodiments, configurations, and aspects, includes providing devices and processes in the absence of items not depicted and/or described herein or in various embodiments, configurations, or aspects hereof, including in the absence of such items as may have been used in previous devices or processes, e.g., for improving performance, achieving ease and\or reducing cost of implementation.
The foregoing discussion of the invention has been presented for purposes of illustration and description. The foregoing is not intended to limit the invention to the form or forms disclosed herein. In the foregoing Detailed Description for example, various features of the invention are grouped together in one or more embodiments, configurations, or aspects for the purpose of streamlining the disclosure. The features of the embodiments, configurations, or aspects of the invention may be combined in alternate embodiments, configurations, or aspects other than those discussed above. This method of disclosure is not to be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment, configuration, or aspect. Thus, the following claims are hereby incorporated into this Detailed Description, with each claim standing on its own as a separate preferred embodiment of the invention.
Moreover, though the description of the invention has included description of one or more embodiments, configurations, or aspects and certain variations and modifications, other variations, combinations, and modifications are within the scope of the invention, e.g., as may be within the skill and knowledge of those in the art, after understanding the present disclosure. It is intended to obtain rights which include alternative embodiments, configurations, or aspects to the extent permitted, including alternate, interchangeable and/or equivalent structures, functions, ranges or steps to those claimed, whether or not such alternate, interchangeable and/or equivalent structures, functions, ranges or steps are disclosed herein, and without intending to publicly dedicate any patentable subject matter.
The present application claims the benefits of U.S. Provisional Application Ser. No. 61/023,757, filed Jan. 25, 2008, of the same title, which is incorporated herein by this reference in its entirety.
| Number | Name | Date | Kind |
|---|---|---|---|
| 4163124 | Jolissaint | Jul 1979 | A |
| 4510351 | Costello et al. | Apr 1985 | A |
| 4567323 | Lottes et al. | Jan 1986 | A |
| 4737983 | Frauenthal et al. | Apr 1988 | A |
| 4797911 | Szlam et al. | Jan 1989 | A |
| 4894857 | Szlam et al. | Jan 1990 | A |
| 5001710 | Gawrys et al. | Mar 1991 | A |
| 5097528 | Gursahaney et al. | Mar 1992 | A |
| 5101425 | Darland | Mar 1992 | A |
| 5155761 | Hammond | Oct 1992 | A |
| 5164981 | Mitchell et al. | Nov 1992 | A |
| 5164983 | Brown et al. | Nov 1992 | A |
| 5167010 | Elm et al. | Nov 1992 | A |
| 5185780 | Leggett | Feb 1993 | A |
| 5206903 | Kohler et al. | Apr 1993 | A |
| 5210789 | Jeffus et al. | May 1993 | A |
| 5274700 | Gechter et al. | Dec 1993 | A |
| 5278898 | Cambray et al. | Jan 1994 | A |
| 5289368 | Jordan et al. | Feb 1994 | A |
| 5291550 | Levy et al. | Mar 1994 | A |
| 5299260 | Shaio | Mar 1994 | A |
| 5309513 | Rose | May 1994 | A |
| 5311422 | Loftin et al. | May 1994 | A |
| 5325292 | Crockett | Jun 1994 | A |
| 5335268 | Kelly, Jr. et al. | Aug 1994 | A |
| 5335269 | Steinlicht | Aug 1994 | A |
| 5390243 | Casselman et al. | Feb 1995 | A |
| 5436965 | Grossman et al. | Jul 1995 | A |
| 5444774 | Friedes | Aug 1995 | A |
| 5467391 | Donaghue, Jr. et al. | Nov 1995 | A |
| 5469503 | Butensky et al. | Nov 1995 | A |
| 5469504 | Blaha | Nov 1995 | A |
| 5473773 | Aman et al. | Dec 1995 | A |
| 5479497 | Kovarik | Dec 1995 | A |
| 5499291 | Kepley | Mar 1996 | A |
| 5500795 | Powers et al. | Mar 1996 | A |
| 5504894 | Ferguson et al. | Apr 1996 | A |
| 5506898 | Costantini et al. | Apr 1996 | A |
| 5530744 | Charalambous et al. | Jun 1996 | A |
| 5537470 | Lee | Jul 1996 | A |
| 5537542 | Eilert et al. | Jul 1996 | A |
| 5544232 | Baker et al. | Aug 1996 | A |
| 5546452 | Andrews et al. | Aug 1996 | A |
| 5555299 | Maloney et al. | Sep 1996 | A |
| 5577169 | Prezioso | Nov 1996 | A |
| 5592378 | Cameron et al. | Jan 1997 | A |
| 5592542 | Honda et al. | Jan 1997 | A |
| 5594726 | Thompson et al. | Jan 1997 | A |
| 5603029 | Aman et al. | Feb 1997 | A |
| 5604892 | Nuttall et al. | Feb 1997 | A |
| 5606361 | Davidsohn et al. | Feb 1997 | A |
| 5611076 | Durflinger et al. | Mar 1997 | A |
| 5627884 | Williams et al. | May 1997 | A |
| 5642515 | Jones et al. | Jun 1997 | A |
| 5673205 | Brunson | Sep 1997 | A |
| 5684872 | Flockhart et al. | Nov 1997 | A |
| 5684964 | Powers et al. | Nov 1997 | A |
| 5689698 | Jones et al. | Nov 1997 | A |
| 5703943 | Otto | Dec 1997 | A |
| 5713014 | Durflinger et al. | Jan 1998 | A |
| 5721770 | Kohler | Feb 1998 | A |
| 5724092 | Davidsohn et al. | Mar 1998 | A |
| 5740238 | Flockhart et al. | Apr 1998 | A |
| 5742675 | Kilander et al. | Apr 1998 | A |
| 5742763 | Jones | Apr 1998 | A |
| 5748468 | Notenboom et al. | May 1998 | A |
| 5749079 | Yong et al. | May 1998 | A |
| 5751707 | Voit et al. | May 1998 | A |
| 5752027 | Familiar | May 1998 | A |
| 5754639 | Flockhart et al. | May 1998 | A |
| 5754776 | Hales et al. | May 1998 | A |
| 5754841 | Carino, Jr. | May 1998 | A |
| 5757904 | Anderson | May 1998 | A |
| 5781614 | Brunson | Jul 1998 | A |
| 5784452 | Carney | Jul 1998 | A |
| 5787410 | McMahon | Jul 1998 | A |
| 5790642 | Taylor et al. | Aug 1998 | A |
| 5790650 | Dunn et al. | Aug 1998 | A |
| 5790677 | Fox et al. | Aug 1998 | A |
| 5794250 | Carino, Jr. et al. | Aug 1998 | A |
| 5796393 | MacNaughton et al. | Aug 1998 | A |
| 5802282 | Hales et al. | Sep 1998 | A |
| 5802510 | Jones | Sep 1998 | A |
| 5818907 | Maloney et al. | Oct 1998 | A |
| 5819084 | Shapiro et al. | Oct 1998 | A |
| 5825869 | Brooks et al. | Oct 1998 | A |
| 5826039 | Jones | Oct 1998 | A |
| 5828747 | Fisher et al. | Oct 1998 | A |
| 5836011 | Hambrick et al. | Nov 1998 | A |
| 5838968 | Culbert | Nov 1998 | A |
| 5839117 | Cameron et al. | Nov 1998 | A |
| 5864874 | Shapiro | Jan 1999 | A |
| 5875437 | Atkins | Feb 1999 | A |
| 5880720 | Iwafune et al. | Mar 1999 | A |
| 5881238 | Aman et al. | Mar 1999 | A |
| 5884032 | Bateman et al. | Mar 1999 | A |
| 5889956 | Hauser et al. | Mar 1999 | A |
| 5897622 | Blinn et al. | Apr 1999 | A |
| 5903641 | Tonisson | May 1999 | A |
| 5903877 | Berkowitz et al. | May 1999 | A |
| 5905793 | Flockhart et al. | May 1999 | A |
| 5909669 | Havens | Jun 1999 | A |
| 5911134 | Castonguay et al. | Jun 1999 | A |
| 5914951 | Bentley et al. | Jun 1999 | A |
| 5915012 | Miloslavsky | Jun 1999 | A |
| 5923745 | Hurd | Jul 1999 | A |
| 5926538 | Deryugin et al. | Jul 1999 | A |
| 5930786 | Carino, Jr. et al. | Jul 1999 | A |
| 5937051 | Hurd et al. | Aug 1999 | A |
| 5937402 | Pandilt | Aug 1999 | A |
| 5940496 | Gisby et al. | Aug 1999 | A |
| 5940839 | Chen et al. | Aug 1999 | A |
| 5943416 | Gisby | Aug 1999 | A |
| 5948065 | Eilert et al. | Sep 1999 | A |
| 5960073 | Kikinis et al. | Sep 1999 | A |
| 5963635 | Szlam et al. | Oct 1999 | A |
| 5963911 | Walker et al. | Oct 1999 | A |
| 5970132 | Brady | Oct 1999 | A |
| 5974135 | Breneman et al. | Oct 1999 | A |
| 5974462 | Aman et al. | Oct 1999 | A |
| 5982873 | Flockhart et al. | Nov 1999 | A |
| 5987117 | McNeil et al. | Nov 1999 | A |
| 5991392 | Miloslavsky | Nov 1999 | A |
| 5996013 | Delp et al. | Nov 1999 | A |
| 5999963 | Bruno et al. | Dec 1999 | A |
| 6000832 | Franklin et al. | Dec 1999 | A |
| 6011844 | Uppaluru et al. | Jan 2000 | A |
| 6014437 | Acker et al. | Jan 2000 | A |
| 6031896 | Gardell et al. | Feb 2000 | A |
| 6038293 | Mcnerney et al. | Mar 2000 | A |
| 6038296 | Brunson et al. | Mar 2000 | A |
| 6044144 | Becker et al. | Mar 2000 | A |
| 6044205 | Reed et al. | Mar 2000 | A |
| 6044355 | Crockett et al. | Mar 2000 | A |
| 6049547 | Fisher et al. | Apr 2000 | A |
| 6049779 | Berkson | Apr 2000 | A |
| 6052723 | Ginn | Apr 2000 | A |
| 6055308 | Miloslavsky et al. | Apr 2000 | A |
| 6064730 | Ginsberg | May 2000 | A |
| 6064731 | Flockhart et al. | May 2000 | A |
| 6084954 | Harless et al. | Jul 2000 | A |
| 6088441 | Flockhart et al. | Jul 2000 | A |
| 6108670 | Weida et al. | Aug 2000 | A |
| 6115462 | Servi et al. | Sep 2000 | A |
| 6128304 | Gardell et al. | Oct 2000 | A |
| 6151571 | Pertrushin | Nov 2000 | A |
| 6154769 | Cherkasova et al. | Nov 2000 | A |
| 6163607 | Bogart et al. | Dec 2000 | A |
| 6173053 | Bogart et al. | Jan 2001 | B1 |
| 6175564 | Miloslavsky et al. | Jan 2001 | B1 |
| 6178441 | Elnozahy | Jan 2001 | B1 |
| 6185292 | Miloslavsky | Feb 2001 | B1 |
| 6185603 | Henderson et al. | Feb 2001 | B1 |
| 6192122 | Flockhart et al. | Feb 2001 | B1 |
| 6215865 | McCalmont | Apr 2001 | B1 |
| 6226377 | Donaghue, Jr. | May 2001 | B1 |
| 6229819 | Darland et al. | May 2001 | B1 |
| 6230183 | Yocom et al. | May 2001 | B1 |
| 6233333 | Dezonmo | May 2001 | B1 |
| 6240417 | Eastwick et al. | May 2001 | B1 |
| 6259969 | Tackett et al. | Jul 2001 | B1 |
| 6263359 | Fong et al. | Jul 2001 | B1 |
| 6272544 | Mullen | Aug 2001 | B1 |
| 6275806 | Pertrushin | Aug 2001 | B1 |
| 6275812 | Haq et al. | Aug 2001 | B1 |
| 6275991 | Erlin | Aug 2001 | B1 |
| 6278777 | Morley et al. | Aug 2001 | B1 |
| 6292550 | Burritt | Sep 2001 | B1 |
| 6295353 | Flockhart et al. | Sep 2001 | B1 |
| 6298062 | Gardell et al. | Oct 2001 | B1 |
| 6307931 | Vaudreuil | Oct 2001 | B1 |
| 6308163 | Du et al. | Oct 2001 | B1 |
| 6324282 | McIllwaine et al. | Nov 2001 | B1 |
| 6332081 | Do | Dec 2001 | B1 |
| 6339754 | Flanagan et al. | Jan 2002 | B1 |
| 6353810 | Pertrushin | Mar 2002 | B1 |
| 6356632 | Foster et al. | Mar 2002 | B1 |
| 6360222 | Quinn | Mar 2002 | B1 |
| 6366666 | Bengtson et al. | Apr 2002 | B2 |
| 6366668 | Borst et al. | Apr 2002 | B1 |
| 6389028 | Bondarenko et al. | May 2002 | B1 |
| 6389132 | Price et al. | May 2002 | B1 |
| 6389400 | Bushey et al. | May 2002 | B1 |
| 6408066 | Andruska et al. | Jun 2002 | B1 |
| 6408277 | Nelken | Jun 2002 | B1 |
| 6411682 | Fuller et al. | Jun 2002 | B1 |
| 6424709 | Doyle et al. | Jul 2002 | B1 |
| 6426950 | Mistry | Jul 2002 | B1 |
| 6427137 | Pertrushin | Jul 2002 | B2 |
| 6430282 | Bannister et al. | Aug 2002 | B1 |
| 6434230 | Gabriel | Aug 2002 | B1 |
| 6446092 | Sutter | Sep 2002 | B1 |
| 6449356 | Dezonno | Sep 2002 | B1 |
| 6449358 | Anisimov et al. | Sep 2002 | B1 |
| 6449646 | Sikora et al. | Sep 2002 | B1 |
| 6453038 | McFarlane et al. | Sep 2002 | B1 |
| 6463148 | Brady | Oct 2002 | B1 |
| 6463346 | Flockhart et al. | Oct 2002 | B1 |
| 6463415 | St. John | Oct 2002 | B2 |
| 6463471 | Dreke et al. | Oct 2002 | B1 |
| 6480826 | Pertrushin | Nov 2002 | B2 |
| 6490350 | McDuff et al. | Dec 2002 | B2 |
| 6499026 | Rivette et al. | Dec 2002 | B1 |
| 6535600 | Fisher et al. | Mar 2003 | B1 |
| 6535601 | Flockhart et al. | Mar 2003 | B1 |
| 6553114 | Fisher et al. | Apr 2003 | B1 |
| 6556974 | D'Alessandro | Apr 2003 | B1 |
| 6560330 | Gabriel | May 2003 | B2 |
| 6560649 | Mullen et al. | May 2003 | B1 |
| 6560707 | Curtis et al. | May 2003 | B2 |
| 6563920 | Flockhart et al. | May 2003 | B1 |
| 6563921 | Williams et al. | May 2003 | B1 |
| 6571285 | Groath et al. | May 2003 | B1 |
| 6574599 | Lim et al. | Jun 2003 | B1 |
| 6574605 | Sanders et al. | Jun 2003 | B1 |
| 6597685 | Miloslavsky et al. | Jul 2003 | B2 |
| 6603854 | Judkins et al. | Aug 2003 | B1 |
| 6604084 | Powers et al. | Aug 2003 | B1 |
| 6614903 | Flockhart et al. | Sep 2003 | B1 |
| 6650748 | Edwards et al. | Nov 2003 | B1 |
| 6662188 | Rasmussen et al. | Dec 2003 | B1 |
| 6668167 | McDowell et al. | Dec 2003 | B2 |
| 6675168 | Shapiro et al. | Jan 2004 | B2 |
| 6684192 | Honarvar et al. | Jan 2004 | B2 |
| 6697457 | Petrushin | Feb 2004 | B2 |
| 6700967 | Kleinoder et al. | Mar 2004 | B2 |
| 6704409 | Dilip et al. | Mar 2004 | B1 |
| 6707903 | Burok et al. | Mar 2004 | B2 |
| 6711253 | Prabhaker | Mar 2004 | B1 |
| 6724885 | Deutsch et al. | Apr 2004 | B1 |
| 6735299 | Krimstock et al. | May 2004 | B2 |
| 6735593 | Williams | May 2004 | B1 |
| 6738462 | Brunson | May 2004 | B1 |
| 6744877 | Edwards | Jun 2004 | B1 |
| 6754333 | Flockhart et al. | Jun 2004 | B1 |
| 6757362 | Cooper et al. | Jun 2004 | B1 |
| 6766013 | Flockhart et al. | Jul 2004 | B2 |
| 6766014 | Flockhart et al. | Jul 2004 | B2 |
| 6766326 | Cena | Jul 2004 | B1 |
| 6775377 | McIllwaine et al. | Aug 2004 | B2 |
| 6785666 | Nareddy et al. | Aug 2004 | B1 |
| 6822945 | Petrovykh | Nov 2004 | B2 |
| 6829348 | Schroeder et al. | Dec 2004 | B1 |
| 6839735 | Wong et al. | Jan 2005 | B2 |
| 6842503 | Wildfeuer | Jan 2005 | B1 |
| 6847973 | Griffin et al. | Jan 2005 | B2 |
| 6898190 | Shtivelman et al. | May 2005 | B2 |
| 6915305 | Subramanian et al. | Jul 2005 | B2 |
| 6947543 | Alvarado et al. | Sep 2005 | B2 |
| 6947988 | Saleh | Sep 2005 | B1 |
| 6963826 | Hanaman et al. | Nov 2005 | B2 |
| 6968052 | Wullert, II | Nov 2005 | B2 |
| 6981061 | Sakakura | Dec 2005 | B1 |
| 6985901 | Sachse et al. | Jan 2006 | B1 |
| 6988126 | Wilcock et al. | Jan 2006 | B2 |
| 7010542 | Trappen et al. | Mar 2006 | B2 |
| 7016919 | Cotton et al. | Mar 2006 | B2 |
| 7020254 | Phillips | Mar 2006 | B2 |
| 7035808 | Ford | Apr 2006 | B1 |
| 7035927 | Flockhart et al. | Apr 2006 | B2 |
| 7039176 | Borodow et al. | May 2006 | B2 |
| 7054434 | Rodenbusch et al. | May 2006 | B2 |
| 7062031 | Becerra et al. | Jun 2006 | B2 |
| 7076051 | Brown et al. | Jul 2006 | B2 |
| 7100200 | Pope et al. | Aug 2006 | B2 |
| 7103562 | Kosiba et al. | Sep 2006 | B2 |
| 7110525 | Heller et al. | Sep 2006 | B1 |
| 7117193 | Basko et al. | Oct 2006 | B1 |
| 7127058 | O'Connor et al. | Oct 2006 | B2 |
| 7136873 | Smith et al. | Nov 2006 | B2 |
| 7149733 | Lin et al. | Dec 2006 | B2 |
| 7155612 | Licis | Dec 2006 | B2 |
| 7158628 | McConnell et al. | Jan 2007 | B2 |
| 7162469 | Anonsen et al. | Jan 2007 | B2 |
| 7165075 | Harter et al. | Jan 2007 | B2 |
| 7170976 | Keagy | Jan 2007 | B1 |
| 7170992 | Knott et al. | Jan 2007 | B2 |
| 7177401 | Mundra et al. | Feb 2007 | B2 |
| 7200219 | Edwards et al. | Apr 2007 | B1 |
| 7203655 | Herbert et al. | Apr 2007 | B2 |
| 7212625 | McKenna et al. | May 2007 | B1 |
| 7215744 | Scherer | May 2007 | B2 |
| 7222075 | Petrushin | May 2007 | B2 |
| 7246371 | Diacakis et al. | Jul 2007 | B2 |
| 7257513 | Lilly | Aug 2007 | B2 |
| 7257597 | Pryce et al. | Aug 2007 | B1 |
| 7266508 | Owen et al. | Sep 2007 | B1 |
| 7283805 | Agrawal | Oct 2007 | B2 |
| 7295669 | Denton et al. | Nov 2007 | B1 |
| 7299259 | Petrovykh | Nov 2007 | B2 |
| 7324954 | Calderaro et al. | Jan 2008 | B2 |
| 7336779 | Boyer et al. | Feb 2008 | B2 |
| 7340408 | Drew et al. | Mar 2008 | B1 |
| 7373341 | Polo-Malouvier | May 2008 | B2 |
| 7376127 | Hepworth et al. | May 2008 | B2 |
| 7392402 | Suzuki | Jun 2008 | B2 |
| 7409423 | Horvitz et al. | Aug 2008 | B2 |
| 7415417 | Boyer et al. | Aug 2008 | B2 |
| 7418093 | Knott et al. | Aug 2008 | B2 |
| 7499844 | Whitman, Jr. | Mar 2009 | B2 |
| 7500241 | Flockhart et al. | Mar 2009 | B1 |
| 7526440 | Walker et al. | Apr 2009 | B2 |
| 7545925 | Williams | Jun 2009 | B2 |
| 7567653 | Michaelis | Jul 2009 | B1 |
| 7580944 | Zhuge et al. | Aug 2009 | B2 |
| 7885209 | Michaelis et al. | Feb 2011 | B1 |
| 20010011228 | Shenkman | Aug 2001 | A1 |
| 20010034628 | Eder | Oct 2001 | A1 |
| 20020019829 | Shapiro | Feb 2002 | A1 |
| 20020021307 | Glenn et al. | Feb 2002 | A1 |
| 20020035605 | McDowell et al. | Mar 2002 | A1 |
| 20020038422 | Suwamoto et al. | Mar 2002 | A1 |
| 20020065894 | Dalal et al. | May 2002 | A1 |
| 20020076010 | Sahai | Jun 2002 | A1 |
| 20020085701 | Parsons et al. | Jul 2002 | A1 |
| 20020087630 | Wu | Jul 2002 | A1 |
| 20020112186 | Ford et al. | Aug 2002 | A1 |
| 20020116336 | Diacakis et al. | Aug 2002 | A1 |
| 20020116461 | Diacakis et al. | Aug 2002 | A1 |
| 20020123923 | Manganaris et al. | Sep 2002 | A1 |
| 20020147730 | Kohno | Oct 2002 | A1 |
| 20030004704 | Baron | Jan 2003 | A1 |
| 20030028621 | Furlong et al. | Feb 2003 | A1 |
| 20030073440 | Mukherjee et al. | Apr 2003 | A1 |
| 20030093465 | Banerjee et al. | May 2003 | A1 |
| 20030108186 | Brown et al. | Jun 2003 | A1 |
| 20030144900 | Whitmer | Jul 2003 | A1 |
| 20030144959 | Makita | Jul 2003 | A1 |
| 20030231757 | Harkreader et al. | Dec 2003 | A1 |
| 20040008828 | Coles et al. | Jan 2004 | A1 |
| 20040015496 | Anonsen | Jan 2004 | A1 |
| 20040015506 | Anonsen et al. | Jan 2004 | A1 |
| 20040054743 | McPartlan et al. | Mar 2004 | A1 |
| 20040057569 | Busey et al. | Mar 2004 | A1 |
| 20040102940 | Lendermann et al. | May 2004 | A1 |
| 20040103324 | Band | May 2004 | A1 |
| 20040138944 | Whitacre et al. | Jul 2004 | A1 |
| 20040162998 | Tuomi et al. | Aug 2004 | A1 |
| 20040193646 | Cuckson et al. | Sep 2004 | A1 |
| 20040202308 | Baggenstoss et al. | Oct 2004 | A1 |
| 20040202309 | Baggenstoss et al. | Oct 2004 | A1 |
| 20040203878 | Thomson | Oct 2004 | A1 |
| 20040210475 | Starnes et al. | Oct 2004 | A1 |
| 20040240659 | Gagle et al. | Dec 2004 | A1 |
| 20040249650 | Freedman et al. | Dec 2004 | A1 |
| 20040260706 | Anonsen et al. | Dec 2004 | A1 |
| 20050021529 | Hodson et al. | Jan 2005 | A1 |
| 20050044375 | Paatero et al. | Feb 2005 | A1 |
| 20050049911 | Engelking et al. | Mar 2005 | A1 |
| 20050065837 | Kosiba et al. | Mar 2005 | A1 |
| 20050071211 | Flockhart et al. | Mar 2005 | A1 |
| 20050071212 | Flockhart et al. | Mar 2005 | A1 |
| 20050071241 | Flockhart et al. | Mar 2005 | A1 |
| 20050071844 | Flockhart et al. | Mar 2005 | A1 |
| 20050091071 | Lee | Apr 2005 | A1 |
| 20050125432 | Lin et al. | Jun 2005 | A1 |
| 20050125458 | Sutherland et al. | Jun 2005 | A1 |
| 20050138064 | Trappen et al. | Jun 2005 | A1 |
| 20050154708 | Sun | Jul 2005 | A1 |
| 20050171968 | Yuknewicz et al. | Aug 2005 | A1 |
| 20050182784 | Trappen et al. | Aug 2005 | A1 |
| 20050261035 | Groskreutz et al. | Nov 2005 | A1 |
| 20050283393 | White et al. | Dec 2005 | A1 |
| 20050289446 | Moncsko et al. | Dec 2005 | A1 |
| 20060004686 | Molnar et al. | Jan 2006 | A1 |
| 20060007916 | Jones et al. | Jan 2006 | A1 |
| 20060015388 | Flockhart et al. | Jan 2006 | A1 |
| 20060026049 | Joseph et al. | Feb 2006 | A1 |
| 20060056598 | Brandt et al. | Mar 2006 | A1 |
| 20060058049 | McLaughlin et al. | Mar 2006 | A1 |
| 20060100973 | McMaster et al. | May 2006 | A1 |
| 20060135058 | Karabinis | Jun 2006 | A1 |
| 20060167667 | Maturana et al. | Jul 2006 | A1 |
| 20060178994 | Stolfo et al. | Aug 2006 | A1 |
| 20060242160 | Kanchwalla et al. | Oct 2006 | A1 |
| 20060256957 | Fain et al. | Nov 2006 | A1 |
| 20060271418 | Hackbarth et al. | Nov 2006 | A1 |
| 20060285648 | Wahl et al. | Dec 2006 | A1 |
| 20070038632 | Engstrom | Feb 2007 | A1 |
| 20070064912 | Kagan et al. | Mar 2007 | A1 |
| 20070083572 | Bland et al. | Apr 2007 | A1 |
| 20070112953 | Barnett | May 2007 | A1 |
| 20070127643 | Keagy | Jun 2007 | A1 |
| 20070156375 | Meier et al. | Jul 2007 | A1 |
| 20070192414 | Chen et al. | Aug 2007 | A1 |
| 20070201311 | Olson | Aug 2007 | A1 |
| 20070201674 | Annadata et al. | Aug 2007 | A1 |
| 20070226231 | Venkat | Sep 2007 | A1 |
| 20070230681 | Boyer et al. | Oct 2007 | A1 |
| 20070239508 | Fazal et al. | Oct 2007 | A1 |
| 20080056165 | Petrovykh | Mar 2008 | A1 |
| 20090193050 | Olson | Jul 2009 | A1 |
| 20090228474 | Chiu et al. | Sep 2009 | A1 |
| Number | Date | Country |
|---|---|---|
| 2143198 | Jan 1995 | CA |
| 2174762 | Jun 1995 | CA |
| 0501189 | Sep 1992 | EP |
| 0576205 | Dec 1993 | EP |
| 0740450 | Oct 1996 | EP |
| 0770967 | May 1997 | EP |
| 0772335 | May 1997 | EP |
| 0829996 | Mar 1998 | EP |
| 0855826 | Jul 1998 | EP |
| 0863651 | Sep 1998 | EP |
| 0866407 | Sep 1998 | EP |
| 0899673 | Mar 1999 | EP |
| 0998108 | May 2000 | EP |
| 1035718 | Sep 2000 | EP |
| 1091307 | Apr 2001 | EP |
| 1150236 | Oct 2001 | EP |
| 1761078 | Mar 2007 | EP |
| 2273418 | Jun 1994 | GB |
| 2290192 | Dec 1995 | GB |
| 2001-053843 | Feb 2001 | JP |
| 2002-304313 | Oct 2002 | JP |
| 2006-054864 | Feb 2006 | JP |
| WO 9607141 | Mar 1996 | WO |
| WO 9728635 | Aug 1997 | WO |
| WO 9856207 | Dec 1998 | WO |
| WO 9917522 | Apr 1999 | WO |
| WO 0026804 | May 2000 | WO |
| WO 0026816 | May 2000 | WO |
| WO 0180094 | Oct 2001 | WO |
| WO 02099640 | Dec 2002 | WO |
| WO 03015425 | Feb 2003 | WO |
| Entry |
|---|
| Shrader, TJ. “Graphical Depiction of Database Table and View Relationships”. Mar. 27, 2005. IP.Com. IP.com No. IPCOM000112744D. pp. 477-480. |
| Koutarou, “Building a Framework for EC using Hibernate, OSWorkflow”, JAVA Press, Japan, Gujutsu Hyouron Company, vol. 25, 2004, pp. 132-147. |
| Microsoft R Access 97 for Windows R Application development guide, Ver. 8.0, Microsoft Corp., a first version, pp. 569-599. |
| Seo, “akuto/FC shop sale assistant systme etc., compressing into halves the number of days for stock possession by a multi-bender EPR plus POS”, Network Computing, Japan Licktelecom Corp., vol. 12, No. 4, Apr. 1, 2000, pp. 45-49. |
| Bischoff et al. “Data Ware House Building Method—practical advices telled by persons having experience and experts”, Kyouritsu Shuppan Corp. May 30, 2000, first edition, pp. 197-216. |
| U.S. Appl. No. 12/569,581, filed Sep. 29, 2009, Michaelis. |
| Blog from “Road warrior and telecommuter—Community for Avaya Users,” from http://www.avayausers.com/showthread.php?p=13430, earliest post date Nov. 21, 2006, printed on Sep. 15, 2009, 4 pages. |
| Google Docs “IP Softphone for Windows Mobile 5” printed on Sep. 15, 2009 from http://docs.google.com/gview?a=v&q=cache:92VrteFXqm8J:support.avaya.com/css/P8/documents/100021136+Avaya+telecom . . . , 1 page. |
| Overview of Avaya IP Softphone printed on Sep. 15, 2009 from http://support.avaya.com/elmodocs2/ip—softphone/Overview—IP—Softphone—R6.htm, 2 pages. |
| Product Brief of “Avaya IP Agent” printed on Sep. 15, 2009 from http://docs.google.com/gview?a=v&q=cache:IRR32Pfzp98J:www.nacr.com/uploadedFiles/Products/Avaya%2520IP%2520Age . . . , 1 page. |
| Product Description of “Avaya one-X Agent,” printed on Sep. 15, 2009 from http://www.avaya.com/usa/product/avaya-one-x-agent, 1 page. |
| Product Overview of “IP Softphone” printed on Sep. 15, 2009 from http://www.nacr.com/Products.aspx?id=236, 3 pages. |
| U.S. Appl. No. 12/789,038, filed May 27, 2010, Bland et al. |
| US 6,537,685, 3/2003, Fisher et al. (withdrawn). |
| U.S. Appl. No. 10/815,534, filed Mar. 31, 2004, Kiefhaber. |
| U.S. Appl. No. 10/815,566, filed Mar. 31, 2004, Kiefhaber. |
| U.S. Appl. No. 10/815,584, filed Mar. 31, 2004, Kiefhaber. |
| U.S. Appl. No. 10/861,193, filed Jun. 3, 2004, Flockhart et al. |
| U.S. Appl. No. 10/946,638, filed Sep. 20, 2004, Flockhart et al. |
| U.S. Appl. No. 11/199,828, filed Aug. 8, 2005, Bland et al. |
| U.S. Appl. No. 11/245,724, filed Oct. 6, 2005, Flockhart et al. |
| U.S. Appl. No. 11/517,646, filed Sep. 7, 2006, Hackbarth et al. |
| U.S. Appl. No. 11/536,546, filed Sep. 28, 2006, Hackbarth et al. |
| U.S. Appl. No. 11/861,857, filed Sep. 26, 2007, Tendick et al. |
| U.S. Appl. No. 12/242,916, filed Oct. 1, 2008, Kiefhaber et al. |
| A.A. Vaisman et al., “A Temporal Query Language for OLAP: Implementation and a Case Study”, LNCS, 2001, vol. 2397, 36 pages. |
| Ahmed, Sarah, “A Scalable Byzantine Fault Tolerant, Secure Domain Name System,” thesis submitted to Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, Jan. 22, 2001, 101 pages. |
| An Expert's Guide to Oracle Technology blog, My Personal Dictionary, Lewis R. Cunningham, posted Mar. 31, 2005, http://blogs.ittoolbox.com/oracle'guide/archives003684.asp, 4 pages. |
| Andy Zmolek; “SIMPLE and Presence: Enterprise Value Propositions,” Avaya presentation, 16 pages, presented Jan. 24, 2002. |
| Aspect—“Analysis and Reporting,” http://aspect.com/products/analysis/index.cfm, (Copyright 2005) (1page). |
| Aspect—“Call Center Reports,” http://aspect.com/products/analysis/ccreporting.cfm, (Copyright 2005) (2 pages). |
| Aspect—“Performance Optimization,” http://aspect.com/products/wfm/performanceopt.cfm?section=performanceopt, (Copyright 2005) (1page). |
| Atkins et a.l; “Common Presence and Instant Messaging: Message Format,” Network Working Group (Jan. 9, 2003), available at http://www.ietf.org/internet-drafts/draft-ietf-impp-cpim-msgfmt-08.txt, 31 pages. |
| Avaya—“Avaya and Blue Pumpkin—Providing Workforce Optimization Solutions” (Copyright 2004) (3 pages). |
| Avaya—“Avaya and Texas Digital Systems—Providing Real-time Access to Call Statistics” (Copyright 2004) (3 pages). |
| Avaya—“Avaya Basic Call Management System Reporting Desktop” (Copyright 2002) (4 pages). |
| Avaya—“Avaya Call Management System” (Copyright 2003) (3 pages). |
| Avaya—“Basic Call Management System Reporting Desktop,” Product Description, http://www.avaya.com/gcm/master-usa/en-us/products/offers/bcmrs—desktop.htm (Copyright 2005) (2 pages). |
| Avaya—“Basic Call Management System Reporting Desktop,” Product Features, http://www.avaya.com/gcm/master-usa/en-us/products/offers/bcmrs—desktop.htm (Copyright 2005) (2 pages). |
| Avaya—“Basic Call Management System Reporting Desktop,” Product Overview, http://www.avaya.com/gcm/master-usa/en-us/products/offers/bcmrs—desktop.htm (Copyright 2005) (2 pages). |
| Avaya—“Basic Call Management System Reporting Desktop,” Product Technical, http://www.avaya.com/gcm/master-usa/en-us/products/offers/bcmrs—desktop.htm (Copyright 2005) (2 pages). |
| Avaya—“Call Management System,” Product Description, http://www.avaya.com/gcm/master-usa/en-us/products/offers/call—management—system.htm (Copyright 2005) (2 pages). |
| Avaya—“Call Management System,” Product Features, http://www.avaya.com/gcm/master-usa/en-us/products/offers/call—management—system.htm (Copyright 2005) (3 pages). |
| Avaya—“Call Management System,” Product Overview, http://www.avaya.com/gcm/master-usa/en-us/products/offers/call—management—system.htm (Copyright 2005) (2 pages). |
| Avaya—“Call Management System,” Product Technical, http://www.avaya.com/gcm/master-usa/en-us/products/offers/call—management—system.htm (Copyright 2005) (2 pages). |
| Avaya—“Multi Channel Product Authorization,” (PA) Version 5.0, (Nov. 2003) (6 pages). |
| Avaya IQ “Introducing Reporting and Analytics as You Designed It”, 2007, 4 pages. |
| Avaya, Inc. Business Advocate Options, at http://www.avaya.com, downloaded on Feb. 15, 2003, Avaya, Inc. 2003. |
| Avaya, Inc. Business Advocate Product Summary, at http://www.avaya.com, downloaded on Feb. 15, 2003, Avaya, Inc. 2003, 3 pages. |
| Avaya, Inc. CentreVu Advocate, Release 9, User Guide, Dec. 2000. |
| Avaya, Inc., “Better Implementation of IP in Large Networks,” Avaya, Inc. 2002, 14 pages. |
| Avaya, Inc., “The Advantages of Load Balancing in the Multi-Call Center Enterprise,” Avaya, Inc., 2002, 14 pages. |
| Avaya, Inc., “Voice Over IP Via Virtual Private Networks: An Overview,” Avaya, Inc., Feb. 2001, 9 pages. |
| Bellsouth Corp., “Frequently Asked Questions—What is a registrar?,” available at https://registration.bellsouth.net/NASApp/DNSWebUI/FAQ.jsp, downloaded Mar. 31, 2003, 4 pages. |
| Berners-Lee et al.; “Uniform Resource Identifiers (URI); Generic Syntax,” Network Working Group, Request for Comments 2396 (Aug. 1998), 38 pages. |
| Bill Michael, “The Politics of Naming” www.cConvergence.com (Jul. 2001) pp. 31-35. |
| Chavez, David, et al., “Avaya MultiVantage Software: Adapting Proven Call Processing for the Transition to Converged IP Networks,” Avaya, Inc., Aug. 2002. |
| Cherry, “Anger Management,” IEEE Spectrum (Apr. 2005) (1 page). |
| Coles, Scott, “A Guide for Ensuring Service Quality in IP Voice Networks,” Avaya, Inc., 2002, pp. 1-17. |
| ComputerWorld, ETL, M. Songini, at http://www.computerworld.com/databasetopics/businessintelligence/datawarehouse/story/ . . . , copyright 2005, 5 pages. |
| Creating and Using Data Warehouse Dimension Tables (Microsoft) copyright 2005, http://msdn.microsoft.com/library/en-us/createdw/createdw—10kz.asp?frame=true, 3 pages. |
| Creating and Using Data Warehouse—Using Dimensional Modeling (Microsoft) downloaded May 18, 2005 http://msdn.microsoft.com/library/en-us/createdw/createdw—39z.asp?frame=true 1 page. |
| Crocker et al.; “Common Presence and Instant Messaging (CPIM),” Network Working Group (Aug. 14, 2002), available at http://www.ietf.org/internet-drafts/draft-ietf-impp-cpim-03.txt, 33 pages. |
| CS 345: Topics in Data Warehousing, Oct. 5, 2004, 36 pages. |
| D. Browning et al., “Data Warehouse Design Considerations”, Microsoft SQL 2000 Technical Articles, Dec. 2001, 24 pages. |
| D. Smith, “Data Model Overview Modeling for the Enterprise While Serving the Individual”, Teredata Global Sales Support, 2007, 33 pages. |
| Data Warehouse—Surrogate Keys, Keep Control Over Record Identifiers by Generating New Keys for the Data Warehouse, Ralph Kimball, May 1998, 4 pages. |
| Data Warehouse Designer—Design Constraints and Unavoidable Realities, No design Problem in School was This Hard, Ralph Kimball, Sep. 3, 2002, 3 pages. |
| Data Warehouse Designer—An Engineer's View—Its' Worthwhile to Remind Ourselves Why We Build Data Warehouses the Way We Do, Ralph Kimball, Jul. 26, 2002, 3 pages. |
| Data Warehouse Designer—Divide and Conquer, Build Your Data Warehouse One Piece at a Time, Ralph Kimball, Oct. 30, 2002, 3 pages. |
| Data Warehouse Designer—TCO Starts with the End User, Ralph Kimball, May 13, 2003, http://www.intelligententerprise.com/030513/608warehouse1—1.jhtml?—requestid=598425, 3 pages. |
| Data Warehouse Designer—The Soul of the Data Warehouse, Part One: Drilling Down, Ralph Kimball, Mar. 20, 2003, 3 pages. |
| Data Warehouse Designer—The Soul of the Data Warehouse, Part Three: Handling Time, Ralph Kimball, Apr. 22, 2003, 3 pages. |
| Data Warehouse Designer—The Soul of the Data Warehouse, Part Two: Drilling Across, Ralph Kimball, Apr. 5, 2003, 3 pages. |
| Data Warehouse Designer—Two Powerful Ideas, The Foundation for Modern Data Warehousing, Ralph Kimball, Sep. 17, 2002, 3 pages. |
| Data Warehouse Designer Fact Tables and Dimension, Jan. 1, 2003, http://www.inteeigententerprise.com/030101/602warehouse1—1.jhtml, Ralph Kimball, 3 page. |
| Dawson et al.; “Vcard MIME Directory Profile,” Network Working Group (Sep. 1998), available at http://www.ietf.org/rfc/rfc2426.txt?number=2426, 40 pages. |
| Dawson, “NPRI's Powerguide, Software Overview” Call Center Magazine (Jun. 1993), p. 85. |
| Day et al.; “A Model for Presence and Instant Messaging,” Network Working Group (Feb. 2000), available at http://www.ietf.org/rfc/rfc2778.txt?number=2778, 16 pages. |
| Day et al.; “Instant Messaging/Presence Protocol Requirements,” Network Working Group (Feb. 2000), available at http://www.ietf.org/rfc/rfc2779.txt?number=2779, 25 pages. |
| Definity Communications System Generic 3 Call Vectoring/Expert Agent Selection (EAS) Guide, AT&T publication No. 555-230-520 (Issue 3, Nov. 1993). |
| E. Noth et al., “Research Issues for the Next Generation Spoken”: University of Erlangen-Nuremberg, Bavarian Research Centre for Knowledge-Based Systems, at http://www5.informatik.uni-erlangen.de/literature/psdir/1999/Noeth99:RIF.ps. gz, 1999, 8 pages. |
| Fielding et al.; “Hypertext Transfer Protocol—HTTP/1.1,” Network Working Group, Request for Comments 2068 (Jan. 1997), 152 pages. |
| Foster, Robin, et al., “Avaya Business Advocate and its Relationship to Multi-Site Load Balancing Applications,” Avaya, Inc., Mar. 2002, 14 pages. |
| Fundamentals of Data Warehousing—Unit 3—Dimensional Modeling, Fundamentals of Data Warehousing, copyright 2005—Evolve Computer Solutions, 55 pages. |
| G. Hellstrom et al., “RFC 2793—RTP Payload for Text Consersation,” Network Working Group Request for Comments 2793 (May 2000), available at http://www.faqs.org/rfcs/rfc2793.html, 8 pages. |
| G. Klyne; “A Syntax for Describing Media Feature Sets,” Network Working Group (Mar. 1999), available at http://www.ietf.org/rfc/rfc2533.txt?number=2533, 35 pages. |
| G. Klyne; “Protocol-independent Content Negotiation Framework,” Network Working Group (Sep. 1999), available at http://www.ietf.org/rfc/rfc2703.txt?number=2703, 19 pages. |
| G. Wiederhold, “Mediation to Deal with Heterogeneous Data Sources”, Stanford University, Jan. 1999, 19 pages. |
| Geotel Communications Corporation Web site printout entitled “Intelligent CallRouter Optimizing the Interaction Between Customers and Answering Resources.”, 1998, 6 pages. |
| Glossary—Curlingstone Publishing, http://www.curlingstone.com/7002/7002glossary.html, downloaded May 24, 2005, 11 pages. |
| Gulbrandsen et al.; “A DNS RR for Specifying the Location of Services (DNS SRV),” Network Working Group (Feb. 2000), available at http://www.ietf.org/rfc/rfc2782.txt?number=2782, 12 pages. |
| H. Schulzrinne et al., “RFC 2833—RTP Payload for DTMF Digits, Telephony Tones and Telephony Signals,” Network Working Group Request for Comments 2833 (May 2000), available at http://www.faqs.org/rfcs/rfc2833.html, 23 pages. |
| Holtman et al.; “HTTP Remote Variant Selection Algorithm—RVSA/1.0,” Network Working Group (Mar. 1998), available at http://www.ietf.org/rfc/rfc2296.txt?number=2296, 13 pages. |
| Holtman et al.; “Transparent Content Negotiation in HTTP,” Network Working Group (Mar. 1998), available at http://www.ietf.org/rfc/rfc2295.txt?number=2295, 55 pages. |
| Intelligent Enterprise Magazine—Data Warehouse Designer: Fact Tables and Dimension, downloaded May 18, 2005, http://www.intelligententerprise.com/030101/602warehouse1—1.jhtml, 7 pages. |
| J. Cahoon, “Fast Development of a Data Warehouse Using MOF, CWM and Code Generation”, CubeModel, May 22, 2006, 32 pages. |
| John H.L. Hansen and Levent M. Arsian, Foreign Accent Classification Using Source Generator Based Prosodic Features, IEEE Proc. ICASSP, vol. 1, pp. 836-839, Detroit USA (May 1995). |
| Karakasidis A. “Queues for Active Data Warehousing”, Jun. 17, 2005, Baltimore, MA, in Proceedings on Information Quality in Informational Systems (IQIS'2005), S.28-39, ISBN: 1-59593-160-0, DOI: 10.1109/DANTE.1999.844938. |
| Kimball, et al., “Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data.” The Data Warehouse ETL Toolkit. 2004. Ch. 5, pp. 170-174. |
| Kimball, et al., “The Complete Guide to Dimensional Modeling.” The Data Warehouse Toolkit. 2nd Edition, 2002. Ch. 11, pp. 240-241. |
| L. Cabibbo et al., “An Architecture for Data Warehousing Supporting Data Independence and Interoperability”, International Journal of Cooperative Information Systems, Nov. 2004, 41 pages. |
| Levent M. Arsian and John H.L. Hansen, Language Accent Classification in American English, Robust Speech Processing Laboratory, Duke University Department of Electrical Engineering, Durham, NC, Technical Report RSPL-96-7, revised Jan. 29, 1996. pp. 1-16. |
| Levent M. Arsian, Foreign Accent Classification in American English, Department of Electrical Computer Engineering, Duke University, Thesis, pp. 1-200 (1996). |
| Microsoft Office Animated Help Tool, date unknown, 1 page. |
| MIT Project Oxygen, Pervasive, Human-Centered Computing (MIT Laboratory for Computer Science) (Jun. 2000) pp. 1-15. |
| Multi-Dimensional Modeling with BW ASAP for BW Accelerator Business Information Warehouse, copyright 2000, 71 pages. |
| NICE Systems—“Insight from Interactions,” “Overwhelmed by the Amount of Data at your Contact Center?” http://www.nice.com/products/multimedia/analyzer.php, (Printed May 19, 2005) (2 pages). |
| NICE Systems—“Multimedia Interaction Products,” “Insight from Interactions,” http://www.nice.com/products/multimedia/contact—centers.php (Printed May 19, 2005) (3 pages). |
| Nortel—“Centrex Internet Enabled Call Centers,” http://www.products.nortel.com/go/product—assoc.jsp?segId=0&parID=0&catID=-9191&rend—id . . . (Copyright 1999-2005) (1page). |
| O. Boussaid et al., “Integration and dimensional modeling approaches for complex data warehousing”, J. Global Optimization, vol. 37, No. 4, Apr. 2007, 2 pages. |
| Presentation by Victor Zue, The MIT Oxygen Project, MIT Laboratory for Computer Science (Apr. 25-26, 2000) 9 pages. |
| Richard Shockey, “ENUM: Phone Numbers Meet the Net” www.cConvergence.com (Jul. 2001) pp. 21-30. |
| Rose et al..; “The APEX Presence Service,” Network Working Group (Jan. 14, 2002), available at http://www.ietf.org/internet-drafts/draft-ietf-apex-presence-06.txt, 31 pages. |
| Sarda, “Temporal Issues in Data Warehouse Systems”, 1999, Database Applications in Non-Traditional Environments (DANTE'99), S. 27, DOI: 10.1109/DANTE.1999.844938. |
| Snape, James, “Time Dimension and Time Zones.” 2004. pp. 1-10. http://www.jamessnape.me.uk/blog/CommentView,gui,79e910a1-0150-4452-bda3-e98d. |
| Stevenson et al.; “Name Resolution in Network and Systems Management Environments”; http://netman.cit.buffalo.edu/Doc/DStevenson/NR-NMSE.html; printed Mar. 31, 2003; 16 pages. |
| Sugano et al. ;“Common Presence and Instant Messaging (CPIM) Presence Information Data Format,” Network Working Group (Dec. 2002), available at http://www.ietf.org/internet-drafts/draft-ietf-impp-cpim-pidf-07.txt, 26 pages. |
| Thayer Watkins, “Cost Benefit Analysis”, 1999, San Jose State University Economics Department, Web Archive http://web.arch ive.org/web/19990225143131/http://www.sjsu.edu/faculty/watkins/cba.htm. |
| The Importance of Data Modeling as a Foundation for Business Insight, Larissa Moss and Steve Hoberman, copyright 2004, 38 pages. |
| “Avaya IQ—Building Upon the Strengths of CMS”, White Paper, Feb. 2007, 11 pages. |
| “Call Center Recording for Call Center Quality Assurance”, Voice Print International, Inc., available at http://www.voiceprintonline.com/call-center-recording.asp?ad—src=google&srch—trm=call—center—monitoring, date unknown, printed May 10, 2007, 2 pages. |
| “Dimensional database”, Wikipedia, downloaded Aug. 30, 2007 (3 pages). |
| “Driving Model Agent Behaviors With Avaya IQ”, White Paper, Apr. 2007, 12 pages. |
| “KANA—Contact Center Support”, available at http://www.kana.com/solutions.php?tid=46, copyright 2006, 3 pages. |
| “Learn the structure of an Access database”, available at http://office.microsoft.com/en-us/access/HA012139541033.aspx, site updated Nov. 13, 2007, pp. 1-4. |
| “Monitoring: OneSight Call Statistics Monitors”, available at http://www.empirix.com/default.asp?action=article&ID=301, date unknown, printed May 10, 2007, 2 pages. |
| “Oracle and Siebel” Oracle, available at http://www.oracle.com/siebel/index.html, date unknown, printed May 10, 2007, 2 pages. |
| “Services for Computer Supported Telecommunications Applications (CSTA) Phase III”; Standard ECMA-269, 5th Edition—Dec. 2002; ECMA International Standardizing Information and Communication Systems; URL: http://www.ecma.ch; pp. 1-666 (Parts 1-8). |
| “Still Leaving It to Fate?: Optimizing Workforce Management”, Durr, William Jr., Nov. 2001. |
| “Access for 9-1-1 and Telephone Emergency Services,” Americans with Disabilities Act, U.S. Department of Justice, Civil Rights Division (Jul. 15, 1998), available at http://www.usdoj.gov/crt/ada/911ta.htm, 11 pages. |
| “Applications, NPRI's Predictive Dialing Package,” Computer Technology (Fall 1993), p. 86. |
| “Call Center Software You Can't Outgrow,” Telemarketing® (Jul. 1993), p. 105. |
| “Domain Name Services,” available at http://www.pism.com/chapt09/chapt09.html, downloaded Mar. 31, 2003, 21 pages. |
| “eGain's Commerce 2000 Platform Sets New Standard for eCommerce Customer Communications,” Business Wire (Nov. 15, 1999)., 3 pages. |
| “Internet Protocol Addressing,” available at http://samspade.org/d/ipdns.html, downloaded Mar. 31, 2003, 9 pages. |
| “Product Features,” Guide to Call Center Automation, Brock Control Systems, Inc., Activity Managers Series™, Section 5—Company B120, p. 59, 1992. |
| “Product Features,” Guide to Call Center Automation, CRC Information Systems, Inc., Tel-ATHENA, Section 5—Company C520, p. 95, 1992. |
| “VAST™, Voicelink Application Software for Teleservicing®,” System Manager User's Guide, Digital Systems (1994), pp. ii, vii-ix, 1-2, 2-41 through 2-77. |
| “When Talk Isn't Cheap,” Sm@rt Reseller, v. 3, n. 13 (Apr. 3, 2000), p. 50. |
| U.S. Appl. No. 11/242,687, filed Oct. 3, 2005, Krimstock et al. |
| Akitsu, “An Introduction of Run Time Library for C Program, the fourth round,” C Magazine, Jul. 1, 1990, vol. 2(7), pp. 78-83. |
| Emura, “Windows API Utilization Guide, Points for Knowledges and Technologies,” C Magazine, Oct. 1, 2005, vol. 17(10), pp. 147-150. |
| Examiner's Office Letter (including translation) for Japanese Patent Application No. 2007-043414, mailed Jul. 7, 2010. |
| Official Action for Canada Patent Application No. 2,639,362, dated Jan. 7, 2013 4 pages. |
| Number | Date | Country | |
|---|---|---|---|
| 20090193050 A1 | Jul 2009 | US |
| Number | Date | Country | |
|---|---|---|---|
| 61023757 | Jan 2008 | US |
