Methods and system for recognizing names in a computer-generated document and for providing helpful actions associated with recognized names

Information

  • Patent Grant
  • 7711550
  • Patent Number
    7,711,550
  • Date Filed
    Tuesday, April 29, 2003
    21 years ago
  • Date Issued
    Tuesday, May 4, 2010
    14 years ago
Abstract
Methods and systems are provided for recognizing names entered into a computer-generated document in the context of a plurality of spoken languages and for providing helpful actions to users upon the recognition of the entered names.
Description
FIELD OF THE INVENTION

The present invention relates generally to text recognition in computer-generated documents. More particularly, embodiments of the present invention relate to methods and systems for recognizing names from a plurality of languages entered into computer-generated documents and for providing helpful actions for use in association with recognized names.


BACKGROUND OF THE INVENTION

Since the advent of the computer and software age, software developers have attempted to provide helpful functionality to software users that is contextual in nature. For example, software has been developed for detecting that a user is entering a date into a computer-generated document as the user is typing the date. Before the user can complete the date, the software application popsup today's date to the user and offers to automatically complete the date for the user. Other software has been developed for offering users helpful actions in response to certain data entered by the user. For example, if the user's word processor application recognizes that the user has entered a date, the user may be offered an action that will launch the user's electronic calendar to allow the user to check appointments or to verify information in her calendar for the entered date.


It would be helpful to users to provide them with actions applicable to names entered in computer-generated documents such as contacts documents, word processing documents, spreadsheet documents, slide presentation documents, calendaring documents, and the like. Unfortunately, names are very difficult to recognize because often names are not distinguishable from any other word in a sentence. And, often names have particular meaning in a relation to the language context in which they are entered. Because of the great diversity of name origins, names may be typed into a document written in one language, for example English, but the name may have its origins in a separate language, for example Chinese.


In addition, modern desktop operating systems are provided with various localization features for improving usability for users throughout the world. For instance, some desktop operating systems provide support for multiple user interface languages. Through this type of support for multiple user interface languages, users can configure the user interface of the operating system, for example, a keyboard, to operate in any of a number of languages supported by the host operating system. Additionally, many application programs also support the use of multiple languages for international users. For example, a word processing program or spreadsheet application program may allow a user to create documents in English, Thai, Vietnamese, or other languages installed in the operating system and enabled by the user. Documents may also be created that contain text or other information in a combination of languages. In fact, international users of such applications frequently create documents that include text in more than one language. Different languages often have vastly different grammatical rules for presenting names. For example, some languages commonly place certain titles before names. Some languages commonly place province or location designation after names.


Accordingly, there is a need for a method and system for recognizing names entered into computer-generated documents according to a variety of different languages and language grammatical rules and for providing helpful actions to a user associated with recognized names. It is with respect to these and other considerations that the present invention has been made.


SUMMARY OF THE INVENTION

Embodiments of the present invention provide methods and systems for recognizing names entered into a computer-generated document in the context of a plurality of spoken languages and for providing helpful actions to users upon the recognition of the entered names.


Generally, a user enters text using a host software application such as a word processor application, a spreadsheet application, a contacts application, a calendaring application, a slide presentation application, and the like. Text entered by the user is passed to a recognizer application. Along with the text, a language designation for the text is passed by the host application if a language designation is known. The recognizer application may be a dynamically-linked library (DLL) application. At the recognizer application, the text is passed to a name recognizer application. The name recognizer may be a separate application plug-in that is associated with the recognizer application, or the name recognizer application may be integrated with the recognizer application.


If the language of text is known, the name recognizer application first breaks the text into words. If the text is not already set out in separate words by known delimiters such as spaces or punctuation marks associated with the known language, the name recognizer may pass the text to a word breaker application for breaking the text into words. According to an embodiment of the present invention. The word breaker application may be integrated with the name recognizer application. Alternatively, the word breaker application may be a separate application that may be called by the name recognizer application when needed.


Once the text is broken into separate words, the name recognizer application applies the grammatical rules of the known language to isolate names from the other words of the text. If one or more names are isolated, they are compared against the user's local or remote contact list for matching names. If the isolated names do not match names contained in a contacts list, the words may be compared against a larger database of names including, for example, names particular to the known language. Alternatively, words of the text may be confirmed as names where the analysis of the words based on the grammatical rules of the known language provides a high probability that a given word or words is a name. Once a word is confirmed as a name, by one of these comparisons or analyses, the name is returned by the recognizer application to the host application. The host application may then tag the name and call on the services of one or more action applications for providing helpful actions to the user when the user subsequently focuses her computer cursor or mouse pointer on the tagged name. For example, the user may be provided actions such as adding the name to a contacts list, deleting the name from a contacts list, sending an email message to the name, and the like.


If the language of the text passed to the recognizer application is not known, the text is broken into words as described above, and each word of the text may be compared directly against a contacts list or larger database of names to determine whether any of the words or combination of words comprise a name. If it may be determined that one or more of the words do comprise a name, the name is returned to the host application, as described above, and helpful actions may be provided in association with the name.


These and other features and advantages, which characterize the present invention, will be apparent from a reading of the following detailed description and a review of the associated drawings. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention as claimed.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 is a block diagram showing the architecture of a personal computer that provides an illustrative operating environment for embodiments of the present invention.



FIG. 2 is a block diagram that shows software architecture for recognizing, labeling, and performing actions on strings of text according to various embodiments of the present invention.



FIG. 3 illustrates a simplified block diagram showing interaction between a host application and a recognizer application and action application for recognizing, labeling, and performing actions on names entered into text according to embodiments of the present invention.



FIG. 4 is a screen diagram showing an exemplary host application text entry screen and showing text entered and recognized as a name according to embodiments of the present invention.



FIGS. 5 and 6 are flow diagrams showing an illustrative routine for recognizing a name in text entered into a computer-generated document and for providing helpful actions associated with the recognized name.





DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

As described briefly above, embodiments of the present invention are directed to methods and systems for recognizing names entered according to a variety of different languages and grammatical rules and for providing helpful actions to a user associated with recognized names. In the following detailed description, references are made to the accompanying drawings that form a part hereof, and in which are shown by way of illustrations specific embodiments or examples. These embodiments may be combined, other embodiments may be utilized, and structural changes may be made without departing from the spirit or scope of the present invention. The following detailed description is therefore not to be taken in a limiting sense and the scope of the present invention is defined by the appended claims and their equivalents.


Referring now to the drawings, in which like numerals represent like elements through the several figures, aspects of the present invention and the exemplary operating environment will be described. FIG. 1 and the following discussion are intended to provide a brief, general description of a suitable computing environment in which the invention may be implemented. While the invention will be described in the general context of program modules that execute in conjunction with an application program that runs on an operating system on a personal computer, those skilled in the art will recognize that the invention may also be implemented in combination with other program modules. Additional aspects of an illustrative operating environment and software architecture for implementing the various embodiments of the present invention are described in U.S. patent application Ser. No. 09/588,411, entitled “Method and System for Semantically Labeling Strings and Providing Actions Based on Semantically Labeled Strings”, which is expressly incorporated herein by reference.


Generally, program modules include routines, programs, components, data structures, and other types of structures that perform particular tasks or implement particular abstract data types. Moreover, those skilled in the art will appreciate that the invention may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and the like. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.


Turning now to FIG. 1, an illustrative computer architecture for a personal computer 2 for practicing the various embodiments of the invention will be described. The computer architecture shown in FIG. 1 illustrates a conventional personal computer, including a central processing unit 4 (“CPU”), a system memory 6, including a random access memory 8 (“RAM”) and a read-only memory (“ROM”) 10, and a system bus 12 that couples the memory to the CPU 4. A basic input/output system containing the basic routines that help to transfer information between elements within the computer, such as during startup, is stored in the ROM 10. The personal computer 2 further includes a mass storage device 14 for storing an operating system 16, application programs, such as the application program 205, and data.


The mass storage device 14 is connected to the CPU 4 through a mass storage controller (not shown) connected to the bus 12. The mass storage device 14 and its associated computer-readable media, provide non-volatile storage for the personal computer 2. Although the description of computer-readable media contained herein refers to a mass storage device, such as a hard disk or CD-ROM drive, it should be appreciated by those skilled in the art that computer-readable media can be any available media that can be accessed by the personal computer 2.


By way of example, and not limitation, computer-readable media may comprise computer storage media and communication media. Computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EPROM, EEPROM, flash memory or other solid state memory technology, CD-ROM, DVD, or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by the computer.


According to various embodiments of the invention, the personal computer 2 may operate in a networked environment using logical connections to remote computers through a TCP/IP network 18, such as the Internet. The personal computer 2 may connect to the TCP/IP network 18 through a network interface unit 20 connected to the bus 12. It should be appreciated that the network interface unit 20 may also be utilized to connect to other types of networks and remote computer systems. The personal computer 2 may also include an input/output controller 22 for receiving and processing input from a number of devices, including a keyboard or mouse (not shown). Similarly, an input/output controller 22 may provide output to a display screen, a printer, or other type of output device.


As mentioned briefly above, a number of program modules and data files may be stored in the mass storage device 14 and RAM 8 of the personal computer 2, including an operating system 16 suitable for controlling the operation of a networked personal computer, such as the WINDOWS XP operating system from MICROSOFT CORPORATION of Redmond, Wash. The mass storage device 14 and RAM 8 may also store one or more application programs. In particular, the mass storage device 14 and RAM 8 may store an application program 205 for creating and editing an electronic document 24. For instance, the application program 205 may comprise a word processing application program a spreadsheet application, a contact application, and the like. Application programs for creating and editing other types of electronic documents may also be used with the various embodiments of the present invention.


Embodiments of the present invention provide program modules for use in conjunction with the application program 205 that recognize names in entered text and provide helpful actions on the recognized names. In particular, embodiments of the invention provide a recognizer plug-in 220 and an action plug-in 225. As will be described in greater detail below, the recognizer plug-in 220 recognizes names in an electronic document 24 and labels the names with semantic information. The name recognizer plug-in 220A then passes this information to the application program 205 for use by the action plug-in 225. The action plug-in 225 performs actions on the recognized names.


According to various embodiments of the present invention, the action plug-in 225 may also generate a list of actions that may be performed on a given name. As a part of this process, the action plug-in 225 may query language settings 26 of the application program 205 or operating system 16. The language settings 26 specify the current user interface language and the currently installed and enabled languages for the application program 205 and the operating system 16. The list of actions may then be customized based on the current user interface language and the installed languages. Additional details regarding the operation of the recognizer plug-in 220 and the action plug-in 225, including the use of the language settings 25 will be described in greater detail below.


Referring now to FIG. 2, an illustrative software architecture for use in conjunction with the various embodiments of the present invention will be described. The architecture shown in FIG. 2 includes an application program 205, such as a word processor application program, a spreadsheet application program, or other type of application program for creating and editing electronic documents. The application program 205 may also comprise a Web browser.


The application program 205 is able to communicate with a recognizer dynamically linked library (“DLL”) 210 and an action DLL 215. As will be described in greater detail below, the recognizer DLL 210 controls one or more recognizer plug-ins 220A-220N and the action DLL 215 controls one or more action plug-ins 225A-225N.


According to one embodiment of the invention, the recognizer plug-ins 220A-220N and the action plug-ins 225A-225N are automation servers. Automation servers are well-known software components that are assembled into programs or add functionality to existing programs running on the WINDOWS XP operating system from MICROSOFT CORPORATION of Redmond, Wash. Automation servers may be written in a variety of computing languages and can be plugged and unplugged at runtime without having to recompile the host program.


The recognizer DLL 210 handles the distribution of text strings from an electronic document being edited by the application program 205 to the individual recognizer plug-ins 220A-220N. The recognizer plug-ins 220A-220N recognizes particular strings in an electronic document, such as a word processing document or a spreadsheet document. The recognizer plug-ins 220A-220N may be packaged with the application program module 205 or they may be written by third parties to recognize particular strings of interest. Typically, the recognizer DLL 210 passes strings to the recognizer plug-ins 220A-220N in single paragraphs or cell value increments. However, strings may be passed to the recognizer plug-ins 220A-220N in other sizes and formats.


As part of recognizing certain strings as including semantic information, the recognizer plug-ins 220A-220N determine which strings are to be labeled and how they are to be labeled. After receiving these results from the various recognizer plug-ins 220, the recognizer DLL 210 sends semantic categories to the application program module 205. According to one actual embodiment of the invention, a name recognizer plug-in 220A is provided for recognizing strings as containing names. Additionally, the recognizer plug-in 220 may return information identifying the location of the name within the text string, including the length of the name.


It should be appreciated that each of the recognizer plug-ins 220A-220N are executed separately. The recognizer DLL 210 is responsible for handling the asynchronicity that results from different recognizer plug-ins 220A-220N returning results at different times. In this manner, various types of data may be recognized within a text string and different actions provided for each semantically labeled string. Additional details regarding the operation of the recognizer plug-in 220 for recognizing numbers will be described below with reference to FIGS. 3-6.


After a string is labeled by a recognizer plug-in 220A-220N, schema information is sent to the application program module 205. A user of the application program module 205 may then execute actions that are associated with the schema information on the recognized string. The action DLL 215 manages the action plug-ins 225A-225N that are executed in order to perform the actions. As with the recognizer plug-ins 220A-22N, the action plug-ins 225A-225N may be packaged with the application program module 205 or written by third parties to perform particular actions that are of interest. The action plug-ins 225A-225N provide possible actions to be presented to the user based upon the schema information, or type label, associated with the string. As will be described in greater detail below, the list of actions provided to the user is dynamically generated for each schema type. This information is then provided to the application program 205 that displays the list of actions to the user when the string is selected.


After an action has been chosen from the list of actions, the action DLL 215 manages the appropriate action plug-in 225A-225N and passes the necessary information between the action plug-in and the application program module 205 so that the action plug-in may execute the desired action. Typically, the application program module 205 sends the action DLL 215 an automation request to invoke the action the user has selected. As will be described in greater detail below, according to one embodiment of the invention, an name action plug-in 225A is provided that provides actions on recognized names. Addition details regarding the operation of the action plug-in 225 will be described in greater detail below with reference to FIGS. 3-6.



FIG. 3 illustrates a simplified block diagram showing interaction between a host application, a recognizer application and an action application for recognizing, labeling, and performing actions on names entered into text according to embodiments of the present invention. According to embodiments of the present invention, and as briefly described above, text entered using the host application 205 is passed to the recognizer DLL 210 that serves as a distribution point for passing text to other recognizer functionality such as the recognizer plug-ins 220A through 220N. According to embodiments of the present invention, the text passed from the host application is directed from the recognizer DLL 210 to a name recognizer 220A. As described above with reference to FIG. 2, the name recognizer 220A may be a plug-in module that is plugged into the recognizer DLL 210 for providing particular functionality, in this case, recognition of names written using a variety of languages.


Referring still to FIG. 3, the name recognizer DLL 220A may compare words in the text received from the host application against a contacts list 330 or against a larger name database 340 to find a matching name. A suitable contacts list database 330 is provided by the Outlook® software application provided by Microsoft Corporation of Redmond, Wash. The name database 340 may include a large database of known names used according to a variety of different languages. Additionally, the name database 340 may also include a list of predictable names associated with particular languages. For example, as is well known to those skilled in the art, certain countries and associated languages have small numbers of names distributed among the populations of those countries. According to embodiments of the present invention, as described in detail below, if the language in which the text is entered is known, that information may be utilized by the name recognizer DLL 220A to compare words against names contained in the database 340 where it is known that certain names associated with the language in which the text is written are common.


Also shown in FIG. 3 is a word breaker application 320. According to embodiments of the present invention, the text received by the name recognizer DLL 220A may be broken into words according to the language in which the text is written. That is, as is well known to those skilled in the art, some languages such as English, Arabic, Hebrew and Hindi use spaces and other delimiters such as punctuation marks to separate words. If text is received by the name recognizer DLL 220A that is already broken into discrete words, the name recognizer 220A may use those words to compare against the contacts list 330 and the name database 340. If the text received by the name recognizer DLL 220A is not broken into discrete words according to the language in which the text has been created, the name recognizer DLL 220A may pass the text to a word breaker application 320 to break the text into discrete words that may be used by the name recognizer DLL 220A for comparison against the contacts list 330 and the name database 340. According to one embodiment of the present invention, the word breaker application 320 may be integrated with the name recognizer DLL 220A. Alternatively, the word breaker application 320 may be a separate application that may be called by the name recognizer application 220A when needed.


According to an embodiment of the present invention, if the language in which the text is created is known, the name recognizer DLL 220A may utilize the grammatical rules and sentence structure rules of the known language to assist the name recognizer DLL 220A in determining which words, if any, in the text received from the host application 205 comprise names. As is known to those skilled in the art, computer operating systems may be configured to allow computers to receive user input and to provide data output according to a variety of different languages. Likewise, host applications 205 often may be configured to receive data input and to provide data output according to a variety of different languages. Accordingly, if the user of the host application 205 configures her computer and the host application 205 to receive data input and to provide data output in a language such as Vietnamese, for example, the host application 205 may pass the designated language to the recognizer DLL 210 along with the text for determining whether any words in the text comprise a name. If the language is known by the name recognizer 220A, the rules of that language may be utilized by the name recognizer 220A to determine whether a word or words comprise a name. For example, if a particular language requires or commonly presents a standard word immediately preceding a name, such as a title noun like “Mr., Ms., Mrs.,” and the like, the name recognizer 220A may utilize that rule in association with the known language to determine that a high probability exists that the word or words immediately following the title noun comprise a name.


Generally, a variety of different grammatical and sentence structure rules exist for many different languages utilized by users of the host application 205. Some languages including English, Arabic, Hebrew and Hindi, utilize word delimiters such as spaces and punctuation marks to separate one word from another. However, these languages don't require or predominately utilize specific grammatical or sentence structure rules relative to names, such as the formal inclusion of a title noun prior to a name, or the inclusion of a province or a location designator after a name. For languages such as these, the name recognizer DLL 220A may know the designated language, but in the absence of specific name oriented rules to the assist the name recognizer DLL, the individual words of text for these languages is compared against the name databases, such as the contacts list 330 and the larger name database 340.


Other languages such as the That language are very formal in nature and typically require or predominately utilize name prefixes or title nouns prior to names, such as Mr. Mrs., Miss, boy, girl, or greeting. For languages such as the That language, the word breaker application 320 may be programmed with a dictionary of the name prefixes or title nouns so that the word breaker application 320 in conjunction with the name recognizer DLL 220A may isolate name prefixes or title nouns in text provided by the host application 205 in order to track a word or words following the name prefix to determine whether those words comprise a name. Other indicators may be utilized by the name recognizer 220A such as the common or maximum numbers of characters, such as vowels and consonants, utilized by a language such as the That language for construction of a name. Inclusion of certain words in some languages may also be used to create an ambiguity by the name recognizer 220A and thus reject a word or words as a name. For example, if a conjunctive word such as “and” or “or” is utilized between two words following a name prefix, for example “Mr. Joe & Sara Smith,” the inclusion of the conjunctive word “and” may be utilized by the name recognizer 220A to determine that the words following the name prefix do not comprise a whole name. Accordingly, nothing will be returned by the name recognizer to the host application 205.


Other languages require or commonly utilize province or location designations immediately following a name. For example, “send this document to Joe Smith of Atlanta” includes a province or location designator of “of Atlanta” immediately following the name. In the case of royal descendents in certain languages, province names such as “Duke of York” or “Prince of Wales” immediately follow names. In either of these cases, the name recognizer 220A may be programmed in conjunction with the word breaker application 320 to recognize province or location designations and then to look to a word or words immediately preceding the province or location designation as having a high probability of comprising a name.


Still other languages, such as the Vietnamese language, typically include family clan names such as “Bui”, or “Phong” immediately preceding a name. Because the number of family clan names is relatively small, the known clan names associated with the language, such as Vietnamese, may be utilized by the word breaker application 320 and the name recognizer 220A for determining whether words immediately following a known clan name comprise a name. In many Far East languages, a relatively small number of common names are held by a majority of the populations originating under those languages. For example, the name “Kim” is a very common name in the Korean population and under the Korean language. Accordingly, common names utilized in such languages may be stored in memory and may be utilized by the word breaker application 320 in conjunction with the name recognizer 220A to quickly compare words of text received from the host application 205 to a list of known common names associated with a known language. In any of the above cases, other general rules may apply. For example, in many languages names are capitalized. Such general rules may be used in conjunction with other more particular rules to assist the name recognizer 220A in confirming that a word of text received from the host application 205 comprises a name.



FIG. 4 is a screen diagram showing an exemplary host application text entry screen and showing text entered and recognized as a name according to embodiments of the present invention. As shown in the exemplary text entry screen 400 of a host application 205, a text string 410 including “please send this document to Joe Smith” is provided. According to embodiments of the present inventions, this text string is passed to the name recognizer 220A via the recognizer DLL 210. According to embodiments of the present invention, the word breaker application 320 is utilized by the name recognizer DLL 220A to parse the text string into individual words. If need be, the word breaker application 320 may parse the text string one character at a time by passing combinations of characters back to the name recognizer DLL 220A for comparing against the databases 330, 340. The word breaker application may also use delimiters such as spaces between the combinations of characters to determine the beginning and ending of individual words. The name recognizer DLL 220A recognizes that the words “Joe Smith” comprise a name and passes those words back to the host application 205 tagged as a name. In response, the words “Joe Smith” in the text string are marked in some manner, such as the underlined marking shown in FIG. 4, to indicate to the user that these words have been associated with some type of additional functionality.


According to an embodiment of the present invention, once the user focuses her computer cursor or mouse pointer over the tagged words, the action DLL 225A associated with names may cause the action window 420 to be opened to provide actions to the user in association with the tagged name. As shown in FIG. 4, the action window 420 includes two actions including “send mail” and “add to contacts.” Accordingly, the user may select one of the provided actions to launch the functionality associated with the action. For example, if the user selects the “add to contacts” action, the user's contacts list provided by the user's calendaring program may be launched to allow the user to add the name “Joe Smith” to the user's contacts list.


Referring still to FIG. 4, a second text string 430 “pleasesendthisdocumenttoJoeSmithofAtlanta” is provided. According to the illustration shown in FIG. 4, this text string has been created according to a language that does not use any type of word delimiters such as spaces or punctuation marks to separate words in the text string. Additionally, the text string 430 includes a province designator “of Atlanta” immediately following the name “Joe Smith”. According to embodiments of the present invention, the word breaker application 320 is utilized by the name recognizer DLL 220A to parse the text string into individual words. If need be, the word breaker application 320 may parse the text string one character at a time by passing combinations of characters back to the name recognizer DLL 220A for comparing against the databases 330, 340. Moreover, as described above with reference to FIG. 3, the name recognizer DLL 220A may have received with the text string an indication of the language in which the text string has been created. The name recognizer DLL 220A then may determine that the language in which the text string is created commonly requires or presents province or location identifiers such as “of Atlanta” immediately following a name. The name recognizer DLL 220A then may use this information to determine that the words “Joe Smith” immediately preceding the province or location identifier “of Atlanta” comprise a name. Because the words “Joe Smith” are passed back to the host application 205 as a name, the action DLL 225A causes the action window 440 to be presented to the user when the user focuses on the marked name “Joe Smith” in the text string 430, as described above. As should be understood, the action items shown in the action windows 420 and 440 are only a small sampling of the actions that may be made available to the user. Other actions include “scheduling and meeting”, “inserting address”, and the like.



FIGS. 5 and 6 are flow diagrams showing an illustrative routine for recognizing a name in text entered into a computer-generated document and for providing helpful actions associated with the recognized name. The method 500 begins at start step 505 and moves to step 510 where a database of names is built for use by the name recognizer 220A in resolving names in text passed to the name recognizer from the host application 205. According to embodiments of the present invention, the database of names may include a contacts list 330 and a separate name database 340, as described above. At step 512, text is input by a user at the host application 205. As described above, the host application 205 may be one of a number of software applications capable of receiving text input from the user. Moreover, the host application 205 may be an application allowing the user to input text according to a variety of languages by selecting an input language using the host application 205 and/or selecting an alternate language user interface via the operating system 16 of the user's computer two.


At step 514, text entered by the user via the host application 205 is passed to the recognizer DLL 210. As should be understood by those skilled in the art, text may be passed to the recognizer DLL in sentences, paragraphs, or other discrete text fractions. Alternatively, text may be passed to the recognizer DLL each time the users goes idle, for example where the user pauses between keystrokes for more than a set time duration.


At step 520, a determination is made as to whether the language of the text passed from the host application 205 is determinable. As described above, if the language of the text passed from the host application 205 has been set by the user via the host application 205 or via the user interface, such as a keyboard, via the user's computer operating system, that information may be passed along with the text selection to the recognizer DLL 210. If the language is determinable, the method proceeds to step 540, and the recognizer DLL passes the text selection and language indicator data to the name recognizer DLL 220A.


At step 540, the text received by the name recognizer 220A is broken into words for the eventual determination as to whether any of the words comprise a name. As described above, according to some languages, the text may already be broken into readily definable words by use of word delimiters such as spaces and punctuation marks. For example, referring back to FIG. 4, the text selection 410 includes a set of words that are separated by spaces. On the other hand, a text selection 430, illustrated in FIG. 4 may be presented to the name recognizer 220A that is created using a language that does not use word delimiters, such as spaces or punctuation marks, where each character is run together in side-by-side orientation. In either case, if necessary, the word breaker application 320 is utilized by the name recognizer 220A for separating the text into words that may be compared against language rules or databases to determine whether any of the words comprise a name. In the case of the text string 430 where the text string is not already broken into definable words, the word breaker 320 may, if necessary, parse the text string one character at a time forming combinations of characters that may be compared against the databases or language rules to determine whether the combinations of characters are words that comprise a name.


At step 542, because the language of the text selection is known, the name recognizer DLL 220A applies the rules of the known language in an attempt to isolate names contained in the text selection passed from the host application 205. For example, referring to the text string 430, illustrated in FIG. 4, if the language of the text string requires or commonly uses a province or location designation immediately after a name, the name recognizer 220A may locate and recognize the phrase “of Atlanta” as a province name or location designator that commonly or by requirement immediately follows a name according to the language of the text selection. Accordingly, the name recognizer 220A may then look to words immediately preceding the phrase “of Atlanta” to determine that a high probability exists that the words immediately preceding the location designator comprise a name.


At step 544, after the name recognizer 220A has applied the rules of the known language to the text selection, a determination is made as to whether the rules comparison allows the name recognizer 220A to resolve any of the words as names. If not, the method may proceed to step 524 where the words of the text selection are compared against the databases 330, 340 in the same manner, as would be words of a text selection where the language of the text selection is not known. If the name recognizer 220A is able to resolve names from the text selection by analyzing the rules of the known language, the method proceeds to step 546. As should be understood by those skilled in the art, the names resolved by the name recognizer 220A by analysis of the rules of the language may not result in an absolute confirmation that a given word or words is a name, but may result in a high probability that a given word or words is a name, and confirmation may be achieved by comparing such words to the user's contact's list 330 or to the other name databases 340. Alternatively, once the name recognizer 220A determines that a sufficient probability exists that a given word or words is a name based on an analysis of the language rules associated with the words, the method may proceed directly to step 534, and the words may be returned to the host application 205 as a name, as will be described in further detail below.


At step 546, the words resolved as a name by the name recognizer by analyzing the language rules associated with the words is compared against the user's contacts list 330. It is useful to compare the words against the user's contacts list 330 because if the words match a name in the user's contact lists 330, actions may ultimately be provided to the user such as sending an email message to the named person. At step 548, FIG. 6, a determination is made as to whether the word or words matches a name contained in the user's contact's list 330. If the words do match a name contained in the user's contacts list 330, the method proceeds to step 534, and the name is returned to the host application 205 as a name, as will be described in detail below. If the words do not match a name contained in the user's contacts list 330, the method proceeds to step 550 and the words are compared against a language-specific name set to determine whether the words match names that are commonly used in the language in which the text string has been created.


At step 552, if the words match names contained in the language-specific set of names, the method proceeds to step 534, and the name is returned to the host application, as described below. If no match is achieved, at step 552, the method proceeds to step 554 and the words are compared against a general database of names 340 where the words are compared against a database containing an exhaustive list of known names. At step 556, if the words match names contained in the general name database, the method proceeds to step 534, and the names are returned to the host application, as described below. If the words do not match any of the databases 330, 340, the method may end at step 595. It should be understood by those skilled in the art that the rules analysis and the comparisons to the databases described above may be done simultaneously or in the order described above. According to an exemplary embodiment of the present invention, the order described above allows for better efficiency in terms of processing time because the words are first compared against databases with the strongest likelihood of matching names.


Referring back to step 520, if the text selection originally passed to the recognizer DLL 210 from the host application 205 does not have an associated known language, the method proceeds to step 520 and the text string is broken into words either using word delimiters such as spaces and/or punctuation marks or by using the word breaker application 320, as described above. As should be understood, a language designation may not have been passed to the recognizer DLL, or the name may be included in a mixed language document. For example, the user may create the document in the English language, but the user may insert Vietnamese based names, for example, throughout the document. In this case, because no particular language is associated with the text passed to the name recognizer 220A, at step 524, each word broken from the text selection is first compared against the user's contacts list 330. At step 526, if any of the words from the text selection match a name or names contained in the user's contacts list 330, the method proceeds to step 534, and the names are passed to the host application 205, as described below. If words broken from the text string do not match names contained in the user's contacts list 330, the method proceeds to step 530, and the words are compared against names contained in a general database 340.


At step 532, FIG. 6, a determination is made as to whether any of the words from the text string passed to the name recognizer 220A match any names contained in the general names database 340. If not, the method may end at step 595. If the words match names contained in the general name database 340, the method proceeds to step 534, and the name is returned to the host application 205.


At step 536, the host application 205 calls the action DLL 215 for actions on the returned name. As illustrated in FIG. 2, according to an embodiment of the present invention, the action DLL 215 may utilize a name action plug-in 225A for providing name-oriented actions on the returned name. At step 538, actions from the action DLL 215 are provided for the returned name. For example, referring to the text string 410, illustrated in FIG. 4, the name “Joe Smith” is marked with an underline or other indicator that the name has been tagged for actions associated with the name. Upon focusing on the tags name by placing the computer cursor or mouse pointer in the tagged name, the action window 420 is made available to the user so that the user can select available actions. As should be understood, the actions made available to the user may be provided dynamically based on the name returned. For example, if the name returned from the name recognizer DLL 220A is a name that matched a name in the user's contacts list 330, an action such as “send mail” may be provided because the electronic mail address associated with the name may be available in the contacts list 330. If the name returned by the name recognizer DLL was not located in the contacts list 330, but was located in a general database 340, an action such as “add to contacts” may be provided to allow the user to add the returned name to the user's contacts list. As should be understood, selection of one of a number of available actions provided to the user may cause some other action, such as the launching of a user interface to allow the user to send an email message, edit a contacts list, prepare a memo, and the like. After actions are provided to the user for the returned name at step 538, the method ends at step 595.


As described herein, methods and systems are provided for recognizing names in a text string entered according to a variety of languages and for providing helpful actions on the recognized name. It will be apparent to those skilled in the art that various modifications or variations may be made in the present invention without departing from the scope or spirit of the invention. Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein.

Claims
  • 1. A method of recognizing names from a text string entered according to one of a plurality of spoken languages for providing helpful actions in association with recognized names, the method being implemented at least in part by a computer and comprising: receiving, by the computer, a previously generated text string;passing the text string to a name recognizer application;determining whether a particular spoken language is associated with the text string;applying a set of name rules of the spoken language associated with the text string to a plurality of individual words comprising the text string, the set of name rules comprising grammatical rules and sentence structure rules in the spoken language;determining whether any of the plurality of individual words comprise a name according to the set of name rules of the spoken language associated with the text string;if any of the plurality of individual words comprise a name, generating a list of user actions that may be performed on the name, wherein generating the list of actions that may be performed on the name comprises, analyzing the language associated with the text string, anddetermining if the name exists in a user contacts database,associating the list of actions with the name,returning the name and the list of user actions associated with the name to a host application with which the text string was previously generated for providing the list of user actions associated with the name, andmarking the name in the text string to indicate actions are available in association with the name; andproviding to a user the list of user actions in association with the name.
  • 2. The method of claim 1, prior to passing the text string to the name recognizer application, passing the text string to a text recognizer application; andpassing the text string from the text recognizer application to the name recognizer application.
  • 3. The method of claim 1, after passing the text string to the name recognizer application, breaking the text string into a plurality of individual words.
  • 4. The method of claim 1, wherein the list of actions in association with the name includes enabling the user to send electronic mail to an electronic mail address associated with the name.
  • 5. The method of claim 1, wherein the list of actions include enabling the user to modify the name in the user contacts database, wherein modify includes any member of the groups comprising: add and delete.
  • 6. The method of claim 1, after determining whether any of the plurality of individual words comprise the name according to the set of name rules of the spoken language associated with the text string, comparing the name to the user contacts database to determine whether the name matches a contact name contained in the user contacts database.
  • 7. The method of claim 6, wherein if the name does not match the contact name contained in the user contacts database, comparing the name to a database of names common to the spoken language associated with the text string.
  • 8. The method of claim 7, wherein if the name does not match a name contained in the database of names common to the spoken language associated with the text string, comparing the name to a general database of names.
  • 9. The method of claim 1, prior to receiving the previously generated text string, building the user contacts database.
  • 10. The method of claim 1, wherein applying the set of name rules of the spoken language associated with the text string to the plurality of individual words comprising the text string, includes determining whether any words in the text string are preceded by a title word.
  • 11. The method of claim 1, wherein applying the set of name rules of the spoken language associated with the text string to the plurality of individual words comprising the text string, includes determining whether any words in the text string are followed by a location designation.
  • 12. The method of claim 1, wherein applying the set of name rules of the spoken language associated with the text string to the plurality of individual words comprising the text string, includes determining whether any words in the text string are preceded by a clan name.
  • 13. A system of recognizing names from a text string entered according to one of a plurality of spoken languages for providing helpful actions in association with recognized names, comprising: a host application operative to receive a previously generated text string;to pass the text string to a name recognizer application;a name recognizer application operative to determine whether a particular spoken language is associated with the text string;to apply a set of name rules of the spoken language associated with the text string to a plurality of individual words comprising the text string, the set of name rules comprising grammatical rules and sentence structure rules of the spoken language;to determine whether any of the plurality of individual words comprise a name according to the set of name rules of the spoken language associated with the text string;to generate a list of user actions that may be performed on the name, in response to the determination whether any of the plurality of individual words comprise a name, wherein generating the list of actions that may be performed on the name comprises analyzing the language associated with the text string and determining if the name exists in a user contacts database;to associate the list of user actions with the name;to return the name and the list of user actions associated with the name to the host application with which the text string was previously generated for providing the list of user actions associated with the name;to mark the name in the text string to indicate the list of user actions are available in association with the name, if any of the plurality of individual words comprise a name; andto provide to a user the list of user actions in association with the name.
  • 14. The system of claim 13, wherein the list of actions associated with the name includes enabling the user to send electronic mail to an electronic mail address associated with the name.
  • 15. The system of claim 13, wherein the list of actions associated with the name include enabling the user to modify the name in the user contacts database, wherein modify includes any member of the groups comprising: add and delete.
  • 16. A computer readable medium containing instructions which when executed by a computer perform the steps of: receiving a previously generated text string;passing the text string to a name recognizer application;determining whether a particular spoken language is associated with the text string;applying a set of name rules of the spoken language associated with the text string to a plurality of individual words comprising the text string, the set of name rules comprising grammatical rules and sentence structure rules of the spoken language;determining whether any of the plurality of individual words comprise a name according to the set of name rules of the spoken language associated with the text string;generating a list of user actions that may be performed on the name, wherein generating the list of actions that may be performed on the name comprises analyzing the language associated with the text string and determining if the name exists in a user contacts database;associating the list of user actions with the name;if any of the plurality of individual words comprise a name, returning the name and the list of user actions associated with the name to a host application with which the text string was previously generated for providing the list of user actions associated with the name,marking the name in the text string to indicate the list of user actions are available in association with the name, andproviding to a user the list of user actions in association with the name.
  • 17. The computer readable medium of claim 16, prior to passing the text string to the name recognizer application, passing the text string to a text recognizer application; and passing the text string from the text recognizer application to the name recognizer application.
  • 18. The computer readable medium of claim 16, after passing the text string to the name recognizer application, breaking the text string into the plurality of individual words.
  • 19. The computer readable medium of claim 16, after returning the name to the host application with which the text was previously generated, passing the name to an action application for providing actions associated with the name.
  • 20. The computer readable medium of claim 16, further comprising upon selection of the marked name in the text string, providing the list of actions associated with the name.
  • 21. The computer readable medium of claim 20, wherein the list of actions associated with the name includes enabling the user to send electronic mail to an electronic mail address associated with the name.
  • 22. The computer readable medium of claim 20, wherein the list of actions associated with the name include enabling the user to modify the name in the user contacts database, wherein modify includes any member of the groups comprising: add and delete.
  • 23. A method of recognizing names from a text string entered according to one of a plurality of spoken languages for providing helpful actions in association with recognized names, the method being implemented at least in part by a computer and comprising: receiving, by the computer, a previously generated text string;passing the text string to a name recognizer application;determining whether a particular spoken language is associated with the text string;applying a set of name rules of the spoken language associated with the text string to a plurality of individual words comprising the text string, the set of name rules comprising grammatical rules and sentence structure rules in the spoken language, wherein applying a set of name rules of a spoken language associated with the text string to a plurality of individual words comprising the text string comprises, determining whether any words in the text string are preceded by a title word,determining whether any words in the text string are followed by a locating designation, anddetermining whether any words in the text string are preceded by a clan name;determining whether any of the plurality of individual words comprise a name according to the set of name rules of the spoken language associated with the text string;if any of the plurality of individual words comprise a name, comparing the name to a user contacts database to determine whether the name matches a contact name contained in the user contacts database,generating a list of user actions that may be performed on the name, wherein generating the list of user actions that may be performed on the name comprises analyzing the language associated with the text string and determining if the name exists in a user contacts database,associating the list of user actions with the name,returning the name and the list of user actions associated with the name to a host application with which the text string was previously generated for providing the list of user actions associated with the name, andmarking the name in the text string to indicate the list of user actions are available in association with the name; andreceiving, by the host application, a selection of the marked name in the text string, and in response to the selection, providing to a user the list of user actions in association with the name.
US Referenced Citations (353)
Number Name Date Kind
4674065 Lange et al. Jun 1987 A
4868750 Kucera et al. Sep 1989 A
5020019 Ogawa May 1991 A
5128865 Sadler Jul 1992 A
5159552 van Gasteren et al. Oct 1992 A
5267155 Buchanan et al. Nov 1993 A
5287448 Nicol et al. Feb 1994 A
5297039 Kanaegami et al. Mar 1994 A
5317546 Balch et al. May 1994 A
5337233 Hofert et al. Aug 1994 A
5341293 Vertelney et al. Aug 1994 A
5351190 Kondo Sep 1994 A
5386564 Shearer et al. Jan 1995 A
5392386 Chalas Feb 1995 A
5418902 West et al. May 1995 A
5446891 Kaplan et al. Aug 1995 A
5522089 Kikinis et al. May 1996 A
5535323 Miller et al. Jul 1996 A
5541836 Church et al. Jul 1996 A
5546521 Martinez Aug 1996 A
5581684 Dudzik et al. Dec 1996 A
5596700 Darnell et al. Jan 1997 A
5617565 Augenbraun et al. Apr 1997 A
5625783 Ezekiel et al. Apr 1997 A
5627567 Davidson May 1997 A
5627958 Potts et al. May 1997 A
5634019 Koppolu et al. May 1997 A
5640560 Smith Jun 1997 A
5657259 Davis et al. Aug 1997 A
5685000 Cox, Jr. Nov 1997 A
5708825 Sotomayor Jan 1998 A
5715415 Dazey et al. Feb 1998 A
5717923 Dedrick Feb 1998 A
5752022 Chiu et al. May 1998 A
5761689 Rayson et al. Jun 1998 A
5764794 Perlin Jun 1998 A
5765156 Guzak et al. Jun 1998 A
5781189 Holleran et al. Jul 1998 A
5781904 Oren et al. Jul 1998 A
5794257 Liu et al. Aug 1998 A
5799068 Kikinis et al. Aug 1998 A
5802253 Gross et al. Sep 1998 A
5802262 Van De Vanter Sep 1998 A
5802299 Logan et al. Sep 1998 A
5802530 van Hoff Sep 1998 A
5805911 Miller Sep 1998 A
5809318 Rivette et al. Sep 1998 A
5815830 Anthony Sep 1998 A
5818447 Wolf et al. Oct 1998 A
5821931 Berquist et al. Oct 1998 A
5822539 Van Hoff Oct 1998 A
5822720 Bookman et al. Oct 1998 A
5826025 Gramlich Oct 1998 A
5832100 Lawton et al. Nov 1998 A
5845077 Fawcett Dec 1998 A
5855007 Jovicic et al. Dec 1998 A
5859636 Pandit Jan 1999 A
5875443 Nielsen Feb 1999 A
5877757 Baldwin et al. Mar 1999 A
5884266 Dvorak Mar 1999 A
5892919 Nielsen Apr 1999 A
5893073 Kasso et al. Apr 1999 A
5893132 Huffman et al. Apr 1999 A
5895461 De La Huerga et al. Apr 1999 A
5896321 Miller et al. Apr 1999 A
5900004 Gipson May 1999 A
5907852 Yamada May 1999 A
5913214 Madnick et al. Jun 1999 A
5920859 Li Jul 1999 A
5924099 Guzak et al. Jul 1999 A
5933139 Feigner et al. Aug 1999 A
5933140 Strahorn et al. Aug 1999 A
5933498 Schneck et al. Aug 1999 A
5940614 Allen et al. Aug 1999 A
5944787 Zoken Aug 1999 A
5946647 Miller et al. Aug 1999 A
5948061 Merriman et al. Sep 1999 A
5956681 Yamakita Sep 1999 A
5974413 Beauregard et al. Oct 1999 A
5987480 Donohue et al. Nov 1999 A
5991719 Yazaki et al. Nov 1999 A
5995756 Hermann Nov 1999 A
6006265 Rangan et al. Dec 1999 A
6006279 Hayes Dec 1999 A
6014616 Kim Jan 2000 A
6018761 Uomini Jan 2000 A
6028605 Conrad et al. Feb 2000 A
6029135 Krasle Feb 2000 A
6029171 Smiga et al. Feb 2000 A
6031525 Perlin Feb 2000 A
6052531 Waldin et al. Apr 2000 A
6061516 Yoshikawa et al. May 2000 A
6067087 Krauss et al. May 2000 A
6072475 Van Ketwich Jun 2000 A
6073090 Fortune et al. Jun 2000 A
6085201 Tso Jul 2000 A
6088711 Fein et al. Jul 2000 A
6092074 Rodkin et al. Jul 2000 A
6108640 Slotznick Aug 2000 A
6108674 Murakami et al. Aug 2000 A
6112209 Gusack Aug 2000 A
6121968 Arcuri et al. Sep 2000 A
6122647 Horowitz et al. Sep 2000 A
6126306 Ando Oct 2000 A
6137911 Zhilyaev Oct 2000 A
6141005 Hetherington et al. Oct 2000 A
6151643 Cheng et al. Nov 2000 A
6154738 Call Nov 2000 A
6167469 Safai et al. Dec 2000 A
6167523 Strong Dec 2000 A
6167568 Gandel et al. Dec 2000 A
6173316 De Boor et al. Jan 2001 B1
6182029 Friedman Jan 2001 B1
6185550 Snow et al. Feb 2001 B1
6185576 McIntosh Feb 2001 B1
6199046 Heinzle et al. Mar 2001 B1
6199081 Meyerzon et al. Mar 2001 B1
6208338 Fischer et al. Mar 2001 B1
6219698 Iannucci et al. Apr 2001 B1
6246404 Feigner et al. Jun 2001 B1
6262728 Alexander Jul 2001 B1
6272074 Winner Aug 2001 B1
6272505 De La Huerga Aug 2001 B1
6282489 Bellesfield et al. Aug 2001 B1
6291785 Koga et al. Sep 2001 B1
6292768 Chan Sep 2001 B1
6295061 Park et al. Sep 2001 B1
6297822 Feldman Oct 2001 B1
6300950 Clark et al. Oct 2001 B1
6308171 De La Huerga Oct 2001 B1
6311152 Bai et al. Oct 2001 B1
6311177 Dauerer et al. Oct 2001 B1
6311194 Sheth et al. Oct 2001 B1
6320496 Sokoler et al. Nov 2001 B1
6323853 Hedloy Nov 2001 B1
6336125 Noda et al. Jan 2002 B2
6336131 Wolfe et al. Jan 2002 B1
6338059 Fields et al. Jan 2002 B1
6339436 Amro et al. Jan 2002 B1
6339755 Hetherington et al. Jan 2002 B1
6347398 Parthasarathy et al. Feb 2002 B1
6349295 Tedesco et al. Feb 2002 B1
6353926 Parthesarathy et al. Mar 2002 B1
6381742 Forbes et al. Apr 2002 B2
6382350 Jezewski et al. May 2002 B1
6392668 Murray May 2002 B1
6396515 Hetherington et al. May 2002 B1
6401067 Lewis et al. Jun 2002 B2
6408323 Kobayashi et al. Jun 2002 B1
6413100 Dickmeyer et al. Jul 2002 B1
6415304 Horvitz Jul 2002 B1
6421678 Smiga et al. Jul 2002 B2
6424979 Livingston et al. Jul 2002 B1
6434567 De La Huerga Aug 2002 B1
6438545 Beauregard et al. Aug 2002 B1
6441753 Montgomery Aug 2002 B1
6442545 Feldman et al. Aug 2002 B1
6442591 Haynes et al. Aug 2002 B1
6456304 Anguilo et al. Sep 2002 B1
6470091 Koga et al. Oct 2002 B2
6473069 Gerpheide Oct 2002 B1
6477510 Johnson Nov 2002 B1
6480860 Monday Nov 2002 B1
6493006 Gourdol et al. Dec 2002 B1
6498982 Bellesfield et al. Dec 2002 B2
6510504 Satyanarayanan Jan 2003 B2
6516321 De La Huerga Feb 2003 B1
6519557 Emens et al. Feb 2003 B1
6519603 Bays et al. Feb 2003 B1
6546433 Matheson Apr 2003 B1
6553385 Johnson et al. Apr 2003 B2
6556972 Bakis et al. Apr 2003 B1
6556984 Zien Apr 2003 B1
6564264 Creswell et al. May 2003 B1
6571241 Nosohara May 2003 B1
6571253 Thompson et al. May 2003 B1
6591260 Schwarzhoff et al. Jul 2003 B1
6595342 Maritzen et al. Jul 2003 B1
6601075 Huang et al. Jul 2003 B1
6604099 Chung et al. Aug 2003 B1
6615131 Rennard et al. Sep 2003 B1
6618733 White et al. Sep 2003 B1
6622140 Kantrowitz Sep 2003 B1
6623527 Hamzy Sep 2003 B1
6625581 Perkowski Sep 2003 B1
6629079 Spiegel et al. Sep 2003 B1
6631519 Nicholson et al. Oct 2003 B1
6636880 Bera Oct 2003 B1
6643650 Slaughter et al. Nov 2003 B1
6654734 Mani et al. Nov 2003 B1
6654932 Bahrs et al. Nov 2003 B1
6658623 Schilit et al. Dec 2003 B1
6687485 Hopkins et al. Feb 2004 B2
6694307 Julien Feb 2004 B2
6697824 Bowman-Amuah Feb 2004 B1
6697837 Rodov Feb 2004 B1
6708189 Fitzsimons et al. Mar 2004 B1
6715144 Daynes et al. Mar 2004 B2
6717593 Jennings Apr 2004 B1
6718516 Claussen et al. Apr 2004 B1
6728679 Strubbe et al. Apr 2004 B1
6732090 Shanahan et al. May 2004 B2
6732361 Andreoli et al. May 2004 B1
6741994 Kang et al. May 2004 B1
6742054 Upton, IV May 2004 B1
6745208 Berg et al. Jun 2004 B2
6766326 Cena Jul 2004 B1
6795808 Strubbe et al. Sep 2004 B1
6802061 Parthasarathy et al. Oct 2004 B1
6826726 Hsing et al. Nov 2004 B2
6829631 Forman et al. Dec 2004 B1
6845499 Srivastava et al. Jan 2005 B2
6857103 Wason Feb 2005 B1
6859908 Clapper Feb 2005 B1
6868625 Szabo Mar 2005 B2
6874125 Carroll et al. Mar 2005 B1
6874143 Murray et al. Mar 2005 B1
6880129 Lee et al. Apr 2005 B1
6883137 Girardot et al. Apr 2005 B1
6898604 Ballinger et al. May 2005 B1
6901402 Corston-Oliver et al. May 2005 B1
6904560 Panda Jun 2005 B1
6925457 Britton et al. Aug 2005 B2
6925470 Sangudi et al. Aug 2005 B1
6944857 Glaser et al. Sep 2005 B1
6948133 Haley Sep 2005 B2
6950831 Haley Sep 2005 B2
6950982 Dourish Sep 2005 B1
6957385 Chan et al. Oct 2005 B2
6963867 Ford et al. Nov 2005 B2
6964010 Sharp Nov 2005 B1
6975983 Fortescue et al. Dec 2005 B1
6976090 Ben-Shaul et al. Dec 2005 B2
6976209 Storisteanu et al. Dec 2005 B1
6981212 Claussen et al. Dec 2005 B1
6986104 Green et al. Jan 2006 B2
6990654 Carroll, Jr. Jan 2006 B2
7003522 Reynar et al. Feb 2006 B1
7013289 Horn et al. Mar 2006 B2
7024658 Cohen et al. Apr 2006 B1
7028312 Merrick et al. Apr 2006 B1
7032174 Montero et al. Apr 2006 B2
7039859 Sundaresan May 2006 B1
7051076 Tsuchiya May 2006 B2
7082392 Butler et al. Jul 2006 B1
7100115 Yennaco Aug 2006 B1
7113976 Watanabe Sep 2006 B2
7146564 Kim et al. Dec 2006 B2
7216351 Maes May 2007 B1
7237190 Rollins et al. Jun 2007 B2
7281245 Reynar et al. Oct 2007 B2
7302634 Lucovsky et al. Nov 2007 B2
7305354 Rodriguez et al. Dec 2007 B2
7392479 Jones et al. Jun 2008 B2
7421645 Reynar Sep 2008 B2
7454459 Kapoor et al. Nov 2008 B1
20010029605 Forbes et al. Oct 2001 A1
20010041328 Fisher Nov 2001 A1
20010042098 Gupta et al. Nov 2001 A1
20010049702 Najmi Dec 2001 A1
20010056461 Kampe et al. Dec 2001 A1
20020002590 King et al. Jan 2002 A1
20020003469 Gupta Jan 2002 A1
20020003898 Wu Jan 2002 A1
20020004803 Serebrennikov Jan 2002 A1
20020007309 Reynar Jan 2002 A1
20020023113 Hsing et al. Feb 2002 A1
20020023136 Silver et al. Feb 2002 A1
20020026450 Kuramochi Feb 2002 A1
20020029304 Reynar et al. Mar 2002 A1
20020035581 Reynar et al. Mar 2002 A1
20020038180 Bellesfield et al. Mar 2002 A1
20020065110 Enns et al. May 2002 A1
20020065891 Malik May 2002 A1
20020066073 Lienhard et al. May 2002 A1
20020078222 Compas et al. Jun 2002 A1
20020091803 Imamura et al. Jul 2002 A1
20020099687 Krishnaprasad et al. Jul 2002 A1
20020100036 Moshir et al. Jul 2002 A1
20020103829 Manning et al. Aug 2002 A1
20020104080 Woodard et al. Aug 2002 A1
20020110225 Cullis Aug 2002 A1
20020111928 Haddad Aug 2002 A1
20020120685 Srivastava et al. Aug 2002 A1
20020129107 Loughran et al. Sep 2002 A1
20020133523 Ambler et al. Sep 2002 A1
20020149601 Rajarajan et al. Oct 2002 A1
20020156774 Beauregard et al. Oct 2002 A1
20020156792 Gombocz et al. Oct 2002 A1
20020169802 Brewer et al. Nov 2002 A1
20020175955 Gourdol et al. Nov 2002 A1
20020178008 Reynar Nov 2002 A1
20020178182 Wang et al. Nov 2002 A1
20020184247 Jokela et al. Dec 2002 A1
20020188941 Cicciarelli et al. Dec 2002 A1
20020196281 Audleman et al. Dec 2002 A1
20020198909 Huynh et al. Dec 2002 A1
20030002391 Biggs Jan 2003 A1
20030005411 Gerken Jan 2003 A1
20030009489 Griffin Jan 2003 A1
20030014745 Mah et al. Jan 2003 A1
20030025728 Ebbo et al. Feb 2003 A1
20030046316 Gergic et al. Mar 2003 A1
20030050911 Lucovsky et al. Mar 2003 A1
20030051236 Pace et al. Mar 2003 A1
20030056207 Fischer et al. Mar 2003 A1
20030081791 Erickson et al. May 2003 A1
20030083910 Sayal et al. May 2003 A1
20030084138 Tavis et al. May 2003 A1
20030097318 Yu et al. May 2003 A1
20030101190 Horvitz et al. May 2003 A1
20030101204 Watson May 2003 A1
20030101416 McInnes et al. May 2003 A1
20030106040 Rubin et al. Jun 2003 A1
20030115039 Wang Jun 2003 A1
20030121033 Peev et al. Jun 2003 A1
20030126136 Omoigui Jul 2003 A1
20030140308 Murthy et al. Jul 2003 A1
20030154144 Pokorny et al. Aug 2003 A1
20030158841 Britton et al. Aug 2003 A1
20030158851 Britton et al. Aug 2003 A1
20030167445 Su et al. Sep 2003 A1
20030172343 Leymaster et al. Sep 2003 A1
20030177341 Devillers Sep 2003 A1
20030182391 Leber et al. Sep 2003 A1
20030192040 Vaughan Oct 2003 A1
20030195937 Kircher et al. Oct 2003 A1
20030212527 Moore et al. Nov 2003 A1
20030220795 Araysantiparb et al. Nov 2003 A1
20030229593 Raley et al. Dec 2003 A1
20030233330 Raley et al. Dec 2003 A1
20040002939 Arora et al. Jan 2004 A1
20040003389 Reynar et al. Jan 2004 A1
20040006564 Lucovsky et al. Jan 2004 A1
20040006741 Radja et al. Jan 2004 A1
20040024875 Horvitz et al. Feb 2004 A1
20040039990 Bakar et al. Feb 2004 A1
20040044959 Shanmugasundaram et al. Mar 2004 A1
20040068694 Kaler et al. Apr 2004 A1
20040083218 Feng Apr 2004 A1
20040133846 Khoshatefeh et al. Jul 2004 A1
20040143581 Bohannon et al. Jul 2004 A1
20040165007 Shafron Aug 2004 A1
20040199861 Lucovsky Oct 2004 A1
20040201867 Katano Oct 2004 A1
20040236717 Demartini et al. Nov 2004 A1
20050050164 Burd et al. Mar 2005 A1
20050055330 Britton et al. Mar 2005 A1
20050094850 Nakao May 2005 A1
20050108195 Yalovsky et al. May 2005 A1
20050120313 Rudd et al. Jun 2005 A1
20050187926 Britton et al. Aug 2005 A1
20060173674 Nakajima et al. Aug 2006 A1
Foreign Referenced Citations (38)
Number Date Country
2 246 920 Mar 2000 CA
200410005390.8 Oct 2008 CN
0 364 180 Apr 1990 EP
0481784 Apr 1992 EP
0598511 May 1994 EP
0872827 Oct 1998 EP
0810520 Dec 1998 EP
1093058 Apr 2001 EP
1280068 Jan 2003 EP
1361523 Nov 2003 EP
1376392 Jan 2004 EP
1 447 754 Aug 2004 EP
64-88771 Apr 1989 JP
05-174013 Jul 1993 JP
08-272662 Oct 1996 JP
09-138636 May 1997 JP
10-171827 Jun 1998 JP
2000-222394 Aug 2000 JP
2000-231566 Aug 2000 JP
2001-014303 Jan 2001 JP
2001-125994 May 2001 JP
2001-522112 Nov 2001 JP
2002-041353 Feb 2002 JP
2002163250 Jun 2002 JP
2002-222181 Aug 2002 JP
2003-141174 May 2003 JP
WO 9507510 Mar 1995 WO
WO 9917240 Apr 1999 WO
WO 0054174 Sep 2000 WO
WO 0067117 Nov 2000 WO
WO 0073949 Dec 2000 WO
WO 0118687 Mar 2001 WO
WO 0137170 May 2001 WO
WO 0186390 Nov 2001 WO
WO 0299627 Jan 2002 WO
WO 0215518 Feb 2002 WO
WO 0242928 May 2002 WO
WO 2004012099 Feb 2004 WO