Abstract: Methods and apparatuses for automatically generating and displaying clustered search results and contextual recommendations are described. While a user is making edits to an electronic document or within an application, a search system may identify a set of search terms based on information entered by the user and/or the locations of the information entered by the user within the electronic document or application and then generate and display search results based on the set of search terms. The search system may cluster search result documents that have a degree of similarity and display multiple clusters of search results to the user. The search system may allow users to specify personalized keyword links and may return a personalized keyword link as a search result for a given search query even if a document or resource referenced by the keyword link has not been indexed or crawled.

Abstract: Methods and apparatuses for improving the scoring and ranking of documents that are responsive to a search query submitted to a search system are described. The search system may utilize a scoring algorithm to score and rank a set of documents that are relevant to the search query. The scoring algorithm may take into consideration topicality, data source affinity, and document popularity. Estimates for both the data source affinity and document popularity may be computed at a group level for different groups within an organization.

Abstract: Methods and apparatuses for automated search evaluation are described. Method include generating, via a first version of a search system, a first set of search results, generating, via a second version of the search system, a second set of search results, identifying one or more differences between the first set of search results and the second set of search results, and selecting between the first version and the second version of the search system based on the one or more differences between the first set of search results and the second set of search results and confidence values associated with at least one search evaluation vector.

Abstract: A system and method for monitoring and optimizing work assistant search engines implemented within secured enterprise computing systems include one or more processing devices to receive diagnostic data of a work assistant search engine from a secured enterprise computing system. The one or more processing devices may further determine, by analyzing the diagnostic data, a search quality metric value associated with the feature values and the scores. Responsive to determining that the search quality metric value differs from a target search quality metric value by a predetermined threshold value, the one or more processing devices may further determine an updated score model, and provide the updated score model to the secured enterprise computing system to update the work assistant search engine.

Abstract: Methods and apparatuses for dynamically generating and applying automated search evaluation sets to improve search results and to automatically detect and correct search system issues are described. A search evaluation set may comprise a set of search evaluation vectors that each map a search query and corresponding properties of the search query to a canonical search result. To detect search system issues over time, baseline search result rankings may be periodically generated or automatically generated after software updates to the search system have been made. Two consecutive baseline search result rankings using the same search evaluation set may then be compared to detect result deviations in search result rankings. If the search system detects that at least a threshold number of result deviations have occurred, then the search system may perform subsequent actions to automatically detect and correct search system issues.

Abstract: A system and method for monitoring and optimizing work assistant search engines implemented within secured enterprise computing systems include one or more processing devices to receive diagnostic data of a work assistant search engine from a secured enterprise computing system. The one or more processing devices may further determine, by analyzing the diagnostic data, a search quality metric value associated with the feature values and the scores. Responsive to determining that the search quality metric value differs from a target search quality metric value by a predetermined threshold value, the one or more processing devices may further determine an updated score model, and provide the updated score model to the secured enterprise computing system to update the work assistant search engine.

Abstract: Methods and apparatuses for dynamically generating and applying automated search evaluation sets to improve search results and to automatically detect and correct search system issues are described. A search evaluation set may comprise a set of search evaluation vectors that each map a search query and corresponding properties of the search query to a canonical search result. To detect search system issues over time, baseline search result rankings may be periodically generated or automatically generated after software updates to the search system have been made. Two consecutive baseline search result rankings using the same search evaluation set may then be compared to detect result deviations in search result rankings. If the search system detects that at least a threshold number of result deviations have occurred, then the search system may perform subsequent actions to automatically detect and correct search system issues.

Abstract: A system and method for monitoring and optimizing work assistant search engines implemented within secured enterprise computing systems include one or more processing devices to receive diagnostic data of a work assistant search engine from a secured enterprise computing system. The one or more processing devices may further determine, by analyzing the diagnostic data, a search quality metric value associated with the feature values and the scores. Responsive to determining that the search quality metric value differs from a target search quality metric value by a predetermined threshold value, the one or more processing devices may further determine an updated score model, and provide the updated score model to the secured enterprise computing system to update the work assistant search engine.