Microsoft Technology Licensing, LLC

Kevin L Haas

Xavier Legros

Rahul Nair

Simon P King

Sandy Wong

Michael Ching

Kang Li

Shubha Umesh Nabar

Derrick Leslie Connell

Jun Yin

Heung Yeung Shum

Wei Mu

Srinivasan Badrinarayanan

Shankar Kalyanaraman

Yi-An Lin

Sameer Indarapu

Search results can include, not only responsive content, typically in the form of documents, but can also include information regarding responsive entities, including tasks relevant to those entities, and can include identifications of individuals from whom additional information can be obtained, or who are otherwise relevant to the search. An association between entities and documents referencing those entities is identified and maintained. Documents responsive to a user's search query are identified utilizing existing algorithmic mechanisms and such identified responsive documents are referenced to determine whether they are associated with one or more entities. Additionally, a people/query mapping is maintained associating individual people with specific queries. User actions directed to one or more people in response to a query are utilized as a feedback loop. User actions directed to one dimension of search results can be utilized to generate updated search queries providing updated search results in other dimensions.

Multidimensional search architecture

Search results may include both objective results and person results. In one example, a search query is evaluated to determine whether it is the type of query that a user might want to ask to a friend. If the query is of such a type, then the search engine may examine a social graph to determine which friends of the user who entered the query may have information that is relevant to answering the query. If such friends exist, then the friends may be displayed along with objective search results, along with an explanation of each friend's relevance to the query. Clicking on a person in the results may cause a conversation to be initiated with that person, thereby allowing the user who entered the query to ask his or her friend about the subject of the query.

Providing objective and people results for search

Methods, systems, and computer-storage media having computer-usable instructions embodied thereon, for prioritizing crawl lists based on social networking rankings are provided. Various scores are associated with users based on a variety of factors including activity levels with respect to social networking services, activity levels with respect to search engines, and interactions with other users in a social networking environment. The scores are used to compute a ranking for the users and, based on the rankings, a crawl list is prioritized such that content associated with the social networking environment is crawled at an appropriate time.

Prioritizing crawl lists using social networking rankings

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Kevin L Haas