Abstract: Systems and methods are directed to generating a synoptic video from one or more documents. The system receives an indication to generate the synoptic video and in response, accesses the one or more documents and user preferences of a user that are derived by the network system. The one or more documents are analyzed to determine relevant text content, whereby the analyzing includes tagging the relevant text content. Based on the user preferences, the system generates the synoptic video that summarizes the tagged relevant text content. The content and style of the synoptic video is based on a user style indicated by the user preferences. For example, the user preference can determine a depth of the summarized content, a type of audio or text used, an amount of images to provide, and an amount of summarized text to provide. The synoptic video can then be displayed to the user.

Abstract: A system and method for securing a portion of a communication includes receiving a request to mark a portion of a communication as sensitive, where the communication includes a sensitive portion and an unsensitive portion. Upon receiving the request, a data property of the sensitive portion is set to a sensitive content property. After setting the data property, the method includes, securing the sensitive portion by initiating security calls for handling the sensitive portion, and transmitting the communication to a recipient. After the communication is transmitted to the recipient, access to the unsensitive portion is provided to the recipient, while the sensitive portion is redacted until the recipient is authenticated for receiving access to the sensitive portion.

Abstract: A system and method for securing a portion of a communication includes receiving a request to mark a portion of a communication as sensitive, where the communication includes a sensitive portion and an unsensitive portion. Upon receiving the request, a data property of the sensitive portion is set to a sensitive content property. After setting the data property, the method includes, securing the sensitive portion by initiating security calls for handling the sensitive portion, and transmitting the communication to a recipient. After the communication is transmitted to the recipient, access to the unsensitive portion is provided to the recipient, while the sensitive portion is redacted until the recipient is authenticated for receiving access to the sensitive portion.

Abstract: Systems and methods are directed to generating a synoptic video from one or more documents. The system receives an indication to generate the synoptic video and in response, accesses the one or more documents and user preferences of a user that are derived by the network system. The one or more documents are analyzed to determine relevant text content, whereby the analyzing includes tagging the relevant text content. Based on the user preferences, the system generates the synoptic video that summarizes the tagged relevant text content. The content and style of the synoptic video is based on a user style indicated by the user preferences. For example, the user preference can determine a depth of the summarized content, a type of audio or text used, an amount of images to provide, and an amount of summarized text to provide. The synoptic video can then be displayed to the user.

Abstract: An example system for linguistic modeling includes a processor and computer memory including instructions that cause the computer processor to receive a voice recording associated with a user. The instructions also cause the processor to extract base phonetics from the received voice recording to generate a set of base phonetics corresponding to the user. The instructions further cause the processor to interact with the user in a style or dialect of the user based on the set of base phonetics corresponding to the user.

Abstract: Techniques and architectures manage tasks in an electronic communications environment, such as in electronic calendars, email accounts, displays, and databases. A computing system may determine a number of task-oriented actions based, at least in part, on a history of execution patterns followed by a particular user for performing particular tasks. Such a history may be generated or modified by a machine learning process. Task-oriented actions may include: prioritizing a set of tasks by using such a history in view of various parameters of each task; extracting an action, subject, and keyword from an individual task; generating a visual cue that represents various parameters of a set of tasks; and generating a productivity report that provides an analysis on the time spent by the user on different task categories.