Abstract: A method for tracking user interactions with an application includes: storing the application in a memory of a mobile device, the application being associated with an instrumented widget and a library, the widget including an event logger; executing the application and the widget; receiving, through a user interface of the mobile device, an input corresponding to the event logger of the widget; logging, by the library, the input corresponding to the event logger of the widget in the memory of the mobile device; filtering a plurality of events, including the input corresponding to the event logger of the widget, to manage what data is reported to a monitor; and transmitting the input corresponding to the event logger of the widget to a server as monitored data.

Abstract: A method of operating a mobile device includes displaying a user interface as an image, the user interface being composed of a plurality of widgets, storing a privacy policy identifying at least one of the widgets, capturing a screenshot image corresponding to the screenshot image, excluding the at least one of the widgets from the screenshot image to create a modified screenshot image, and transmitting the modified screenshot image over a network to a monitoring server.

Abstract: A system includes a user model module that generates a plurality of topic-specific user knowledge models for each user of a plurality of users, each topic-specific user knowledge model representing a level of knowledge possessed by a respective user on a single topic from a set of globally defined topics shared among the plurality of users, a expertise model building module that generates a plurality of topic-specific expert knowledge models, each topic-specific expert knowledge model representing an aggregate level of knowledge possessed by a plurality of expert users on a single topic from a set of globally defined topics shared among the plurality of users, and a processor of a computer that executes instructions for comparing the topic-specific user knowledge model of the first user with the topic-specific expert knowledge model for a respective topic to determine a distance between a user knowledge level and an aggregate expert knowledge level for the topic.

Abstract: A method includes generating, as executed by a processor on a computer, a plurality of topic-specific user knowledge models for each user of a plurality of users, each topic-specific user knowledge model representing a level of knowledge possessed by a respective user on a single topic from a set of globally defined topics shared among the plurality of users, generating a plurality of topic-specific expert knowledge models, each topic-specific expert knowledge model representing an aggregate level of knowledge possessed by a plurality of expert users on a single topic from a set of globally defined topics shared among the plurality of users, comparing the topic-specific user knowledge model of the first user with the topic-specific expert knowledge model for a respective topic to determine a distance between a user knowledge level and an aggregate expert knowledge level for the topic.

Abstract: A method for performing program analysis includes receiving programs of a first platform that have been assigned a first label and programs of the first platform that have been assigned a second label. Each of the programs of the first platform is expressed as platform-independent logical features. A discriminatory model or classifier is trained, using machine learning, based on the expression of the programs of the first platform as platform-independent logical features, to distinguish between programs of the first label and programs of the second label. An unlabeled program of a second platform is received and is expressed as platform-independent logical features. The trained discriminatory model or classifier is used to determine if the unlabeled program warrants the first label or the second label, based on the expression of the unlabeled program as platform-independent logical features.

Abstract: A method for performing program analysis includes receiving programs of a first platform that have been assigned a first label and programs of the first platform that have been assigned a second label. Each of the programs of the first platform is expressed as platform-independent logical features. A discriminatory model or classifier is trained, using machine learning, based on the expression of the programs of the first platform as platform-independent logical features, to distinguish between programs of the first label and programs of the second label. An unlabeled program of a second platform is received and is expressed as platform-independent logical features. The trained discriminatory model or classifier is used to determine if the unlabeled program warrants the first label or the second label, based on the expression of the unlabeled program as platform-independent logical features.

Abstract: A method includes storing an application in a memory of a mobile device, wherein the application is associated with a widget including an event logger and a library managing the widget, executing, by the mobile device, the application and the widget, receiving, through a user interface of the mobile device, an input corresponding to the event logger of the widget, logging, by the library, the input corresponding to the event logger of the widget in the memory of the mobile device, and reporting, by the library, the input corresponding to the event logger of the widget to a remote monitoring server as monitored data.

Abstract: A method for tracking user interactions with an application includes: storing the application in a memory of a mobile device, the application being associated with an instrumented widget and a library, the widget including an event logger; executing the application and the widget; receiving, through a user interface of the mobile device, an input corresponding to the event logger of the widget; logging, by the library, the input corresponding to the event logger of the widget in the memory of the mobile device; filtering a plurality of events, including the input corresponding to the event logger of the widget, to manage what data is reported to a monitor; and transmitting the input corresponding to the event logger of the widget to a server as monitored data.

Abstract: A method includes storing an application in a memory of a mobile device, wherein the application is associated with a widget including an event logger and a library managing the widget, executing, by the mobile device, the application and the widget, receiving, through a user interface of the mobile device, an input corresponding to the event logger of the widget, logging, by the library, the input corresponding to the event logger of the widget in the memory of the mobile device, and reporting, by the library, the input corresponding to the event logger of the widget to a remote monitoring server as monitored data.

Abstract: A method of operating a mobile device includes displaying a user interface as an image, the user interface being composed of a plurality of widgets, storing a privacy policy identifying at least one of the widgets, capturing a screenshot image corresponding to the screenshot image, excluding the at least one of the widgets from the screenshot image to create a modified screenshot image, and transmitting the modified screenshot image over a network to a monitoring server.

Abstract: A method for performing program analysis includes receiving programs of a first platform that have been assigned a first label and programs of the first platform that have been assigned a second label. Each of the programs of the first platform is expressed as platform-independent logical features. A discriminatory model or classifier is trained, using machine learning, based on the expression of the programs of the first platform as platform-independent logical features, to distinguish between programs of the first label and programs of the second label. An unlabeled program of a second platform is received and is expressed as platform-independent logical features. The trained discriminatory model or classifier is used to determine if the unlabeled program warrants the first label or the second label, based on the expression of the unlabeled program as platform-independent logical features.

Abstract: A method for performing program analysis includes receiving programs of a first platform that have been assigned a first label and programs of the first platform that have been assigned a second label. Each of the programs of the first platform is expressed as platform-independent logical features. A discriminatory model or classifier is trained, using machine learning, based on the expression of the programs of the first platform as platform-independent logical features, to distinguish between programs of the first label and programs of the second label. An unlabeled program of a second platform is received and is expressed as platform-independent logical features. The trained discriminatory model or classifier is used to determine if the unlabeled program warrants the first label or the second label, based on the expression of the unlabeled program as platform-independent logical features.

Abstract: A method modifies an application program to create an augmented application program by including at least one call and a software library in the application program. The at least one call is to a method that forms part of the library. The method further includes, upon receiving a request from an augmented application program resident on the device, registering and authenticating the augmented application program and sending a policy file to the device that is configured to control use of only the augmented application program. Another method receives at a device an application program augmented to include the at least one call and software library. The method further includes launching the application program and sending a registration and authentication request to a server of an enterprise, and receiving from the server a policy file configured for controlling use by the device of only the registered and authenticated augmented application program.

Abstract: A system includes a user model module that generates a plurality of topic-specific user knowledge models for each user of a plurality of users, each topic-specific user knowledge model representing a level of knowledge possessed by a respective user on a single topic from a set of globally defined topics shared among the plurality of users, a expertise model building module that generates a plurality of topic-specific expert knowledge models, each topic-specific expert knowledge model representing an aggregate level of knowledge possessed by a plurality of expert users on a single topic from a set of globally defined topics shared among the plurality of users, and a processor of a computer that executes instructions for comparing the topic-specific user knowledge model of the first user with the topic-specific expert knowledge model for a respective topic to determine a distance between a user knowledge level and an aggregate expert knowledge level for the topic.

Abstract: A method includes generating, as executed by a processor on a computer, a plurality of topic-specific user knowledge models for each user of a plurality of users, each topic-specific user knowledge model representing a level of knowledge possessed by a respective user on a single topic from a set of globally defined topics shared among the plurality of users, generating a plurality of topic-specific expert knowledge models, each topic-specific expert knowledge model representing an aggregate level of knowledge possessed by a plurality of expert users on a single topic from a set of globally defined topics shared among the plurality of users, comparing the topic-specific user knowledge model of the first user with the topic-specific expert knowledge model for a respective topic to determine a distance between a user knowledge level and an aggregate expert knowledge level for the topic.

Abstract: A method modifies an application program to create an augmented application program by including at least one call and a software library in the application program. The at least one call is to a method that forms part of the library. The method further includes, upon receiving a request from an augmented application program resident on the device, registering and authenticating the augmented application program and sending a policy file to the device that is configured to control use of only the augmented application program. Another method receives at a device an application program augmented to include the at least one call and software library. The method further includes launching the application program and sending a registration and authentication request to a server of an enterprise, and receiving from the server a policy file configured for controlling use by the device of only the registered and authenticated augmented application program.

Abstract: Automatically generating a meeting digest of a set of meetings is provided. A set of topics of interest to the parties to the set of meetings is detected utilizing a user model associated with a user that is based on at least one of communications, relationships, and roles of the parties to the set of meetings. Topic-related content associated with the set of topics of interest to the parties is extracted from meeting data corresponding to the set of meetings. Then, the meeting digest of the set of meetings is generated using the topic-related content associated with the set of topics of interest to the parties extracted from the meeting data corresponding to the set of meetings.

Abstract: Business outcome-based personalized ranking of information objects is provided. Information objects in outcome-based business processes are ranked by recording information objects generated during a creation of the outcome-based business processes. At least one business process comprises an outcome attribute, and at least one business process comprises in-process information objects. A composite graph is generated of the information objects and business processes. Each node in the graph corresponds to an information object or a business process. Links between two information object nodes have a strength based on a content similarity and a social network distance. The in-process information object node connects to a corresponding business process node, and two business process nodes have a link if they are indicated as related in the business process information system. The information objects are ranked based on the link strengths.

Abstract: Methods and apparatus are provided for business outcome-based personalized ranking of information objects. Information objects in outcome-based business processes are ranked by recording information objects generated during a creation of the outcome-based business processes. At least one business process comprises an outcome attribute, and at least one business process comprises in-process information objects. A composite graph is generated of the information objects and business processes. Each node in the graph corresponds to an information object or a business process. Links between two of the information object nodes have a strength based on a content similarity and a social network distance. The in-process information object node connects to a corresponding business process node, and two business process nodes have a link if they are indicated as related in the business process information system.

Abstract: Automatically generating a meeting digest of a set of meetings is provided. A set of topics of interest to the parties to the set of meetings is detected utilizing a user model associated with a user that is based on at least one of communications, relationships, and roles of the parties to the set of meetings. Topic-related content associated with the set of topics of interest to the parties is extracted from meeting data corresponding to the set of meetings. Then, the meeting digest of the set of meetings is generated using the topic-related content associated with the set of topics of interest to the parties extracted from the meeting data corresponding to the set of meetings.