Abstract: Techniques are described for providing automated recommendations of real-world locations, such as businesses, for users to visit based at least in part on historical location-preference information. The historical location-preference information used by the recommendation system may include the historical location-preference information of the person that requests the recommendation, other people explicitly identified as participants by the requestor, and/or other people implicitly determined to be participants. The historical location-preference information may be explicit, such as “check-ins” or reviews, or implicit. Implicit participants may be identified in a variety of ways, including social network relationships and the context in which the recommendation request is submitted.

Abstract: Techniques described herein describe a schema and taxonomy matching process that uses clicklogs to map a schema for source data to a schema for target data. A search engine may receive source data that is structured using the source schema, and the search engine itself may contain target data structured using the target schema. Using query distributions derived from the clicklogs, the source schema may be mapped to the target schema. The mapping can be used to integrate the source data into the target data and to index the integrated data for a search engine.