Abstract: Functionality is described for identifying a discussion topic based on user interest information. The user interest information may originate from one or more sources, such as the user's search-related behavior. The functionality then provides an opportunity for the user to engage in a communication exchange associated with the identified discussion topic.

Abstract: The automatic search engine recommendation technique described herein automatically recommends topic-specific search engines for user queries. In one embodiment, it automatically matches each query submitted to a non-topic specific or general search engine with one or more vertical search engines using a recommendation model and a set of features. For a given query, one embodiment of the technique suggests vertical search engines and topic-specific search results along with the search results from the general search engine.

Abstract: Architecture that automatically detects historical search contexts as well as behaviors related to a search query. Machine learning and hand-authored rules are employed to automatically identify search contexts. Historical information likely to be useful in the current context is surfaced. When a user enters a search query or executes another search behavior, past behaviors are exposed which are contextually related to the current behavior. The architecture also provides automatic discovery of historical contexts, features related to the contexts, and training or authoring of a system for classifying behavior into contexts, using some combination of the machine learning and/or hand-authored rules. A runtime system classifies the current user behavior into a context and surfaces contextual information to the user.

Abstract: This patent application pertains to dynamic search interaction. One example includes an organizational component configured to obtain a search query from a user. The organizational component can also be configured to obtain related search queries. The organizational component can further be configured to organize the related search queries by topic and to estimate a relative likelihood that an intent of the user matches an individual topic. This example also includes an image generation component configured to cause the organized related search queries to be presented on a graphical user interface (GUI) in a manner that reflects the relative likelihood.

Abstract: Described is a search technology in which a search engine constructs a results page for a query that integrates suggested queries with the individual query results (e.g., displayed URLs). When rendered, the proximity of the suggested queries to their corresponding individual query result provides context as to the specific URL to which the suggested query is related. Suggested queries may appear alongside their associated search result, e.g., a displayed URL, and/or in an expandable panel proximate that individual search result. Suggested queries may appear within text accompanying a URL, and/or in a drop down menu following interaction with such text or the like. Related queries may be found by using a search result URL to find a query, by analyzing a search result's text snippet, by accessing historical data, and/or by accessing current user session data.

Abstract: Architecture that automatically detects historical search contexts as well as behaviors related to a search query. Machine learning and hand-authored rules are employed to automatically identify search contexts. Historical information likely to be useful in the current context is surfaced. When a user enters a search query or executes another search behavior, past behaviors are exposed which are contextually related to the current behavior. The architecture also provides automatic discovery of historical contexts, features related to the contexts, and training or authoring of a system for classifying behavior into contexts, using some combination of the machine learning and/or hand-authored rules. A runtime system classifies the current user behavior into a context and surfaces contextual information to the user.

Abstract: This patent application pertains to dynamic search interaction. One example includes an organizational component configured to obtain a search query from a user. The organizational component can also be configured to obtain related search queries. The organizational component can further be configured to organize the related search queries by topic and to estimate a relative likelihood that an intent of the user matches an individual topic. This example also includes an image generation component configured to cause the organized related search queries to be presented on a graphical user interface (GUI) in a manner that reflects the relative likelihood.

Abstract: The automatic search engine recommendation technique described herein automatically recommends topic-specific search engines for user queries. In one embodiment, it automatically matches each query submitted to a non-topic specific or general search engine with one or more vertical search engines using a recommendation model and a set of features. For a given query, one embodiment of the technique suggests vertical search engines and topic-specific search results along with the search results from the general search engine.

Abstract: Described is a search technology in which a search engine constructs a results page for a query that integrates suggested queries with the individual query results (e.g., displayed URLs). When rendered, the proximity of the suggested queries to their corresponding individual query result provides context as to the specific URL to which the suggested query is related. Suggested queries may appear alongside their associated search result, e.g., a displayed URL, and/or in an expandable panel proximate that individual search result. Suggested queries may appear within text accompanying a URL, and/or in a drop down menu following interaction with such text or the like. Related queries may be found by using a search result URL to find a query, by analyzing a search result's text snippet, by accessing historical data, and/or by accessing current user session data.

Abstract: Functionality is described for identifying a discussion topic based on user interest information. The user interest information may originate from one or more sources, such as the user's search-related behavior. The functionality then provides an opportunity for the user to engage in a communication exchange associated with the identified discussion topic.

Abstract: A component presents access to a recommended search provider via a user interface element. In an example embodiment, a device-implemented method for recommending a search provider includes acts of receiving, ascertaining, and modifying. A search query input is received. A recommended search provider is ascertained at least partially responsive to the search query input. A user interface is modified to indicate the recommended search provider.