Abstract: Representative embodiments disclose mechanisms to complete partial queries entered by a user. Users enter a partial query. The partial query is used to search a short text index comprising the titles of documents. The search yields a list results. The top k entries of the list are selected and a language model is created from the top k entries. The language model comprises n-grams from the top k entries and an associated probability for each n-gram. A query completion generator creates query completion suggestions by matching n-grams with the partial query, removing candidate suggestions that to not comply with suggestion rules, and filtering the remaining suggestions according to a filtering criteria. The top N results are returned as suggestions to complete the query.

Abstract: Examples are disclosed that relate to deferring a message based upon a target situation for message presentation. One example provides a computing device including an output subsystem including one or more output devices, an input subsystem including one or more user input devices, and a logic device. The computing device further includes memory storing instructions executable by the logic device to receive a message from a remote computing system, output a notification of the message via the output subsystem, and receive via the input subsystem a request for a deferral of the message, the request for the deferral including an annotation to be stored for a later presentation with the message.

Abstract: Non-limiting examples of the present disclosure describe low latency pre-web classification of query data. In examples, processing is performed where query data may be analyzed in a low latency manner that includes providing a vertical intent classification and entity identification for query data before a web ranking service processes the query data. Query data may be received. A vertical intent classification index may be searched using the query data. In examples, the vertical intent classification index may comprise a set of files that can be used to determine one or more candidate entity identifiers for the query data. The one or more entity identifiers may be ranked. The query data, a vertical intent classification for the vertical intent classification index and the one or more ranked candidate entity identifiers may be transmitted for processing associated with a web ranking service. Other examples are also described.

Abstract: Examples are disclosed that relate to deferring a message based upon a target situation for message presentation. One example provides a computing device including an output subsystem including one or more output devices, an input subsystem including one or more user input devices, and a logic device. The computing device further includes memory storing instructions executable by the logic device to receive a message from a remote computing system, output a notification of the message via the output subsystem, and receive via the input subsystem a request for a deferral of the message, the request for the deferral including an annotation to be stored for a later presentation with the message.

Abstract: Representative embodiments disclose mechanisms to complete partial natural language questions. Users enter a partial question. The system comprises a plurality of indexes, one index comprising common phrases associated with natural language questions and other indexes comprising short text entries associated with documents, such as document titles. The partial question is used to search one or more of the indexes. The search yields a ranked list of results. The top k entries of the list are selected and one or more language models are created from the top k entries. Each language model comprises n-grams from the top k entries from an index and an associated probability for each n-gram. A question completion generator creates question completion suggestions by matching n-grams with the partial question, removing ungrammatical candidate suggestions, and filtering the remaining suggestions per a filtering criteria. The top N results are returned as suggestions to complete the question.

Abstract: Representative embodiments disclose mechanisms to complete partial queries entered by a user. Users enter a partial query. The partial query is used to search a short text index comprising the titles of documents. The search yields a list results. The top k entries of the list are selected and a language model is created from the top k entries. The language model comprises n-grams from the top k entries and an associated probability for each n-gram. A query completion generator creates query completion suggestions by matching n-grams with the partial query, removing candidate suggestions that to not comply with suggestion rules, and filtering the remaining suggestions according to a filtering criteria. The top N results are returned as suggestions to complete the query.

Abstract: Representative embodiments disclose mechanisms to complete partial natural language questions. Users enter a partial question. The system comprises a plurality of indexes, one index comprising common phrases associated with natural language questions and other indexes comprising short text entries associated with documents, such as document titles. The partial question is used to search one or more of the indexes. The search yields a ranked list of results. The top k entries of the list are selected and one or more language models are created from the top k entries. Each language model comprises n-grams from the top k entries from an index and an associated probability for each n-gram. A question completion generator creates question completion suggestions by matching n-grams with the partial question, removing ungrammatical candidate suggestions, and filtering the remaining suggestions per a filtering criteria. The top N results are returned as suggestions to complete the question.

Abstract: Non-limiting examples of the present disclosure describe low latency pre-web classification of query data. In examples, processing is performed where query data may be analyzed in a low latency manner that includes providing a vertical intent classification and entity identification for query data before a web ranking service processes the query data. Query data may be received. A vertical intent classification index may be searched using the query data. In examples, the vertical intent classification index may comprise a set of files that can be used to determine one or more candidate entity identifiers for the query data. The one or more entity identifiers may be ranked. The query data, a vertical intent classification for the vertical intent classification index and the one or more ranked candidate entity identifiers may be transmitted for processing associated with a web ranking service. Other examples are also described.

Abstract: Systems, methods, and computer-readable storage media for providing query-completion suggestions that include answers to the complete queries suggested while the user is formulating a search query. At least a portion of a search query is received by the search engine. As the portion of the search query is received, query-completion suggestions are identified and answers to the plausible search query completions are identified for inclusion in the search input area. Upon selection of a query-completion suggestion, the search engine results page is presented, wherein the search engine results page includes the answers in the snippets generated for the results that contain the answers to the completed queries suggested to the user.

Abstract: A computer-implemented system for the retrieval and manipulation of information available via an information network includes an information retrieval and processing component. The information retrieval and processing component includes: (a) search query means for conducting a search of the information network to obtain references to the information relevant to a search query; (b) information retrieval means for retrieving information available from sources on the information network, and an information store, for storage of retrieved information; and (c) processing means for processing of information retrieved from sources on the information network, and of information stored in the information store, to produce corresponding processed information.

Abstract: The author ranking technique described herein is a technique to rank authors in social media systems along various dimensions, using a variety of statistical methods for utilizing those dimensions. More particularly, the technique ranks authors in social media systems through a combination of statistical techniques that leverage usage metrics, and social and topical graph characteristics. In various exemplary embodiments, the technique can rank author authority by the following: 1) temporal analysis of link sharing in which authority is computed based on a user's propensity to provide early links to web pages that subsequently become popular; 2) topical authority based on the author's links and content updates in specific topic areas; and 3) popularity and influence based on nodal properties of authors.

Abstract: Systems, methods, and computer-readable storage media for providing query-completion suggestions that include answers to the complete queries suggested while the user is formulating a search query. At least a portion of a search query is received by the search engine. As the portion of the search query is received, query-completion suggestions are identified and answers to the plausible search query completions are identified for inclusion in the search input area. Upon selection of a query-completion suggestion, the search engine results page is presented, wherein the search engine results page includes the answers in the snippets generated for the results that contain the answers to the completed queries suggested to the user.

Abstract: A computer-implemented system for the retrieval and manipulation of information available via an information network includes an information retrieval and processing component. The information retrieval and processing component includes: (a) search query means for conducting a search of the information network to obtain references to the information relevant to a search query; (b) information retrieval means for retrieving information available from sources on the information network, and an information store, for storage of retrieved information; and (c) processing means for processing of information retrieved from sources on the information network, and of information stored in the information store, to produce corresponding processed information.

Abstract: Various technologies described herein pertain to using social activity data to personalize ranking of results returned by a computing operation for a user. For each of the results returned by the computing operation, a respective first affinity of the user to a corresponding result and a respective second affinity of the user to the corresponding result can be calculated and used for ranking the results. The respective first affinity of the user to the corresponding result can be calculated based on correlations between social activity data of the user and social activity data of a first group of historical users that clicked the corresponding result. Moreover, the respective second affinity of the user to the corresponding result can be calculated based on correlations between the social activity data of the user and social activity data of a second group of historical users that skipped the corresponding results.

Abstract: A computer-implemented system for the retrieval and manipulation of information available via, an information network includes an information retrieval and processing component. The information retrieval and processing component includes: (a) search query means for conducting a search of the information network to obtain references to the information relevant to a search query; (b) information retrieval means for retrieving information available from sources on the information network, and an information store, for storage of retrieved information; and (c) processing means for processing of information retrieved from sources on the information network, and of information stored in the information store, to produce corresponding processed information.

Abstract: An aggregation service aggregates discussions of events and topics within a given subject area using seed search queries, seed URLs, and/or search engine data. A subject area is selected and a set of seed search queries and/or seed URLs relevant to that subject area are manually generated. The set of seed search queries and/or seed URLs are used to identify URLs containing content relevant to the subject area. The URLs are crawled at given intervals to identify content items, which are analyzed using a classifier to identify content items relevant to the subject area. The content items are grouped into clusters surrounding events and/or topics within the subject area. The various clusters are ranked against one another to facilitate ordering clusters for presentation to end-users.

Abstract: Various technologies described herein pertain to using social activity data to personalize ranking of results returned by a computing operation for a user. For each of the results returned by the computing operation, a respective first affinity of the user to a corresponding result and a respective second affinity of the user to the corresponding result can be calculated and used for ranking the results. The respective first affinity of the user to the corresponding result can be calculated based on correlations between social activity data of the user and social activity data of a first group of historical users that clicked the corresponding result. Moreover, the respective second affinity of the user to the corresponding result can be calculated based on correlations between the social activity data of the user and social activity data of a second group of historical users that skipped the corresponding results.

Abstract: A search engine configured to respond to a search query with a search results page is presented. The search engine includes at least one annotated search result in the search results page. The at least one annotated search results is annotated according to user data independent of the basis by which the search results are identified. The search results page is generated to include user-actionable controls by which a user can update the search results according to update criteria. The update criteria is used in a feedback loop to improve the user data upon which search results are personalized and/or annotated.

Abstract: The subject disclosure is directed towards building one or more context and query models representative of users' search interests based on their logged interaction behaviors (context) preceding search queries. The models are combined into an intent model by learning an optimal combination (e.g., relative weight) for combining the context model with a query model for a query. The resultant intent model may be used to perform a query-related task, such as to rank or re-rank online search results, predict future interests, select advertisements, and so forth.

Abstract: The author ranking technique described herein is a technique to rank authors in social media systems along various dimensions, using a variety of statistical methods for utilizing those dimensions. More particularly, the technique ranks authors in social media systems through a combination of statistical techniques that leverage usage metrics, and social and topical graph characteristics. In various exemplary embodiments, the technique can rank author authority by the following: 1) temporal analysis of link sharing in which authority is computed based on a user's propensity to provide early links to web pages that subsequently become popular; 2) topical authority based on the author's links and content updates in specific topic areas; and 3) popularity and influence based on nodal properties of authors.