Abstract: Systems, methods, and computer-readable storage media are provided for inferring missing or ambiguous attribute values for entities based on partial information about such entities and/or information about other similar entities as extracted from multiple information sources for generating Web ranking signals for online search. A plurality of heterogeneous input data sources are ingested and combined to produce output data having information content that is more than the sum of its parts. A generic platform is provided where multiple data sources having information content related to entity attributes can be plugged-in without additional changes being necessary to the platform. This generic plugin model for extracting and inferring entity attribute values makes it easy to leverage new data sources as they become available to improve the final inferred attribute data.

Abstract: Systems, methods, and computer-readable storage media are provided for permitting users to search the content of a plurality of apps from a single search query input location. A user inputs a search query and a plurality of apps and/or the content thereof is searched to determine relevancy to the input query. If an app having relevant app content is identified, it may be determined if the app is associated with the querying user. If it is determined that the app is associated with the querying user, the information determined relevant to the input query may be presented to the user. If, it is determined that the app is not associated with the user, the user may be presented with the identity of the app and/or be directed to a location (e.g., an app store) where the user can become associated with the identified app and obtain the desired information.

Abstract: Systems, methods, and computer-readable storage media are provided for inferring missing or ambiguous attribute values for entities based on partial information about such entities and/or information about other similar entities as extracted from multiple information sources for generating Web ranking signals for online search. A plurality of heterogeneous input data sources are ingested and combined to produce output data having information content that is more than the sum of its parts. A generic platform is provided where multiple data sources having information content related to entity attributes can be plugged-in without additional changes being necessary to the platform. This generic plugin model for extracting and inferring entity attribute values makes it easy to leverage new data sources as they become available to improve the final inferred attribute data.

Abstract: Systems, methods, and computer-readable storage media are provided for inferring missing or ambiguous attribute values for entities based on partial information about such entities and/or information about other similar entities as extracted from multiple information sources for generating Web ranking signals for online search. A plurality of heterogeneous input data sources are ingested and combined to produce output data having information content that is more than the sum of its parts. A generic platform is provided where multiple data sources having information content related to entity attributes can be plugged-in without additional changes being necessary to the platform. This generic plugin model for extracting and inferring entity attribute values makes it easy to leverage new data sources as they become available to improve the final inferred attribute data.

Abstract: Systems, methods, and computer-readable storage media are provided for adjusting presentation characteristics of a search engine results page (SERP) by a client device based on a query intent of a user. The client may forward a search prefix to a search service and in response receive one or more query suggestions and one or more machine learning algorithms configured to each query suggestion. The user executes a search query comprising the query intent by selecting one of the query suggestions. The client device computes scores for each result group using the machine learning algorithm configured for the selected query suggestion. At least one presentation characteristic of the SERP is adjusted so that at least one result group is emphasized over another based on the respective result group scores representing a relevance to the query intent.

Abstract: Systems, methods, and computer-readable storage media are provided for permitting users to search the content of a plurality of apps from a single search query input location. A user inputs a search query and a plurality of apps and/or the content thereof is searched to determine relevancy to the input query. If an app having relevant app content is identified, it may be determined if the app is associated with the querying user. If it is determined that the app is associated with the querying user, the information determined relevant to the input query may be presented to the user. If, it is determined that the app is not associated with the user, the user may be presented with the identity of the app and/or be directed to a location (e.g., an app store) where the user can become associated with the identified app and obtain the desired information.

Abstract: Systems, methods, and computer-readable storage media are provided for inferring missing or ambiguous attribute values for entities based on partial information about such entities and/or information about other similar entities as extracted from multiple information sources for generating Web ranking signals for online search. A plurality of heterogeneous input data sources are ingested and combined to produce output data having information content that is more than the sum of its parts. A generic platform is provided where multiple data sources having information content related to entity attributes can be plugged-in without additional changes being necessary to the platform. This generic plugin model for extracting and inferring entity attribute values makes it easy to leverage new data sources as they become available to improve the final inferred attribute data.