Microsoft Technology Licensing, LLC

Nishchay Kumar

Vipindeep Vangala

Ankur Hayatnagarkar

Nitin Pande

Rashi Anand

Rajesh Gunda

Madan Gopal Jhanwar

Tulasi Menon

Suryanarayana Shastri

Sapna Grover

Swati Valecha

Rahul Gupta

Abhijit Rao

Juan Diego Ferre

Justin Varacheril George

Sangita N Pitre

Long Qiu

Rafael Barcelos

Sandeep Kadiyala

Sibabrata Paladhi

Raunak Oberoi

Giselli Panontini De Souza

Sundar Srinivasan

Julien J T Pierre

Prabuddh Jaiswal

A computing system obtain a keyword and an identifier for a user of a content authoring application. Based upon the keyword and identifier for the user, the computing system walks a user graph comprising nodes connected by edges. The walk comprises identifying seed nodes in the user graph representing at least one topic that corresponds to the keyword and identifying second level nodes in the user graph that are connected to the seed nodes. The second level nodes represent first content that is associated with the user. The computing system transmits contextual data that is based upon the first content to the content authoring application. The contextual data is processed and formatted and is included in second content presentable by the content authoring application. The contextual data may be used to autogenerate the second content without user input. The second content may be modified by the user as desired.

Artificial intelligence driven personalization for content authoring applications

A method of generating a unified graph is described. First graph data is received from a first data source, nodes within the first graph data including first, second, and third fields. Second graph data is received from a second data source, nodes within the second graph data including first, second, and fourth fields. The unified graph is generated from the first and second graph data using aggregated fields of the first field and the third field as a unique identifier of a unified schema for nodes within the unified graph having a first type and aggregated fields of the first field and the fourth field as a unique identifier of the unified schema for nodes within the unified graph having a second type, wherein nodes of the unified graph represent entities and edges of the unified graph represent relationships among the entities.

Unified graph generation

This disclosure provides a system and method for providing intelligently-selected collections of user-centric content in a web browser. When implemented as a method, the method includes maintaining a user-centric graph with a plurality of user-centric facts derived from user interaction with different computer services. The method further includes recognizing different contexts of interest to the user. For each context, a collection of user-centric facts pertaining to the context are recognized in the user-centric graph, such recognition being based on a relationship between user-centric facts in the user-centric graph. The method further includes, for each context, displaying intelligently-selected content based on the collection of user-centric facts.

User-centric browser location

An intelligent task assistant program can identify tasks associated with a user over a reporting period based on an analysis of, and inferences drawn from, data associated with one or more personal information programs, such as an electronic calendar application, an electronic reminder application, an electronic collaborative application, and/or an electronic communication application. The task assistant may also prioritize the identified tasks based on content associated with the tasks. Some or all of the prioritized tasks can be provided to an output device for perception by the user.

Providing task assistance to a user

A computerized personal assistant communicatively couples to a computer database including a plurality of available skills for the computerized personal assistant. The computerized personal assistant recognizes a current context of the user. The computerized personal assistant operates a previously-trained machine learning classifier to assess a match confidence for a candidate skill, the match confidence indicating a quality of match between the current context and a reference context previously associated with the candidate skill. The computerized personal assistant executes instructions defining an assistive action associated with the candidate skill responsive to the match confidence exceeding a predefined match confidence threshold. The computerized personal assistant executes the instructions defining a complementary help action associated with the candidate skill responsive to the match confidence not exceeding the predefined match confidence threshold.

Skill discovery for computerized personal assistant

A method for providing contextual information to a user during a browsing session includes maintaining a user-centric graph including a plurality of user-centric facts associated with the user and derived from interaction by the user with a plurality of different computer services. The method further includes recognizing a context of interaction with a browser application by a user. The method further includes identifying assistive information pertaining to the context, and displaying the assistive information to the user. The assistive information may be based at least on one or more user-centric facts in the user-centric graph.

User-centric contextual information for browser

Techniques and technologies for cross-device task execution are described. In at least some embodiments, a system includes a processing component configured to: receive device information associated with a networked group of devices; receive user preference information indicating one or more user preferences for performing one or more tasks; receive an indication of a task to be performed; select a designated device of the networked group of devices associated with the user to perform the task based at least partially on the user preference information; and transmit the task to be performed to the designated device.

Cross-device task execution

Growing community of inventors

Hyderabad Telangana, India

Nishchay Kumar