Microsoft Technology Licensing, LLC

Chun-Kai Wang

Emre Mehmet Kiciman

Yi-Min Wang

Johnson T Apacible

Kuansan Wang

Francislav Petrov Penov

Li-wei He

Silviu-Petru Cucerzan

Wissam S Kazan

Bo-June Hsu

Felipe Luis Naranjo

Xiaoxin Yin

Aaron C Hoff

Aleksey Sinyagin

Gilad Lotan

Wenzhao Tan

Sreeharsha Kamireddy

Danah Boyd

Paul Oka

Yi-Chin Tu

Wissam Kazan

Technologies described herein relate to receiving data from a social networking application, wherein the data is generated by a first individual, and executing an entity extraction algorithm to extract at least one entity from the received data. A hyperlink is displayed on a computing device utilized by a second individual, wherein the hyperlink is based at least in part upon the at least one entity, and the hyperlink is configured to direct the first individual to a search engine and is further configured to cause the search engine to execute a search that pertains to the at least one entity.

Generating activities based upon social data

A method described herein includes acts of extracting at least one entity from an arbitrary web page being viewed by an individual on a computing device and comparing the at least one entity with social network data of the individual, wherein the social network data comprises a plurality of messages generated by members of a social network of the individual. The method further includes the acts of identifying at least one message in the plurality of messages based at least in part upon the comparing of the at least one entity with the social network data of the individual and causing the at least one message to be displayed on the web page in conjunction with the at least one entity.

Social browsing

Technologies pertaining to the creation of personalized data for an individual, including personalized data based on a social networking participant's social networking data, entity extraction, and automatic collage generation are described herein. In one implementation, the personalized data is used to provide a personalized, social-based replacement for a default UI element. In one implementation, a disambiguated named entity is extracted from user generated content in a social networking application, a socially interesting photomontage is automatically generated based on photographs from a social networking application, and the photomontage is rendered with hotspots containing socially relevant annotations.

Social home page

Techniques that may be used for detecting a primary content (e.g., a web page) that the user is viewing and presenting one or more pieces of supplemental content (e.g., social media data) together with the primary content. The supplemental content presented to the user together with the primary content may be content that is matched to the primary content and therefore detected to be relevant to the user. Detection of primary content and matching to supplemental content may be carried out based on a comparison of entities related to the primary and supplemental content. In some embodiments, an analysis of the primary content for entities may include ordering entities according to significance in the primary content and selecting top entities for comparison. Also, in some embodiments, multiple pieces of supplemental content may be displayed to a user categorized based on entity.

Presenting supplemental content in context

A question associated with a first user may be obtained. A search link may be determined based on content of the first question. A response may be obtained. Updates to a content graph may be initiated, including an addition of a question node and a first link indicating asking of the question by the first user, and an addition of a response node and a second link indicating an answer relationship between the question and the response, and a third link indicating answering of the question from a second user, the second user associated with the first user via a friend link indicating a friend connection relationship between nodes associated with the first user and the second user.

Mobile social interaction

A crowdsourcing data structuring system and method for capturing unstructured data from the Web and adding structure by placing the data in a document that is accessible by others in a cloud computing environment. Using crowdsourcing, the unstructured data is annotated, amended, and verified to add structure to the unstructured data. An anchor and update module convert the data to a pointer that links the document to the data at an information source and stores the pointer in the document rather than the data itself. The data displayed in the document is updated whenever the information source is updated. A contribution module allows users to add data to the document, a validation module allows users to determine the validity of the data linked to in the document, and an expert ranking module allows users to rank the expert or contributor of the data in the document.

Structuring unstructured web data using crowdsourcing

A question associated with a first user may be obtained. A search link may be determined based on content of the first question A response may be obtained. Updates to a content graph may be initiated, including an addition of a question node and a first link indicating asking of the question by the first user, and an addition of a response node and a second link indicating an answer relationship between the question and the response, and a third link indicating answering of the question from a second user, the second user associated with the first user via a friend link indicating a friend connection relationship between nodes associated with the first user and the second user.

A method described herein includes acts of receiving data from a social networking application, wherein the data is generated by a first individual, and executing an entity extraction algorithm to extract at least one entity from the received data. The method also includes automatically causing a hyperlink to be displayed on a computing device utilized by a second individual, wherein the hyperlink is based at least in part upon the at least one entity, wherein the hyperlink is configured to direct the first individual to a search engine and is further configured to cause the search engine to execute a search that pertains to the at least one entity.

A resource selection system is described for assisting a user in performing a task that includes multiple actions. At each stage of the task, the system presents a set resources from which the user may select to perform a subsequent action in the task. The system implicitly selects the set of resources based on context information that identifies the user's current informational needs. For example, the context information may be derived from textual information that is being presented on a user device, which the user is presumed to be viewing at the current time. In one implementation, the system selects the set of resources by computing language models for respective domains and respective entities. The system uses the language models to determine the relevance of the context information to each of the domains. The system then selects resources associated with domains that have been assessed as relevant.

Growing community of inventors

Bellevue, WA, United States of America

Chun-Kai Wang