Google Inc.

Neha Arora

Ke Yang

Zuguang Yang

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing local search results. In one aspect, a method determines a first local document in a set of local documents for search results is eligible for a demotion operation. The determination is based at least in part on a proximity measure based on the location of the user device and a location specified for the first local document. In response to the determination, for each other local documents in the set of local documents, a proximity measure location of the user device and the location specified for the other local document is determined. The first local document is demoted in its ranking when at least one of the proximity measures indicates a respective other local document has a specified location that is within a threshold distance of the location of the user device.

Distance based search ranking demotion

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for enforcing the category diversity or sub-category diversity of POIs that are identified in response to a local search. According to one implementation, a method includes receiving a request to identify points of interest (POIs), obtaining data identifying (i) candidate points of interest (POIs) that satisfy the request, (ii) a respective category associated with each candidate POI, and (iii) a non-scaled score associated with each candidate POI, and ranking, for each of one or more of the categories, the candidate POIs associated with the category, based on the respective non-scaled scores. The method also includes scaling, for each of the one or more categories, the non-scaled scores of the ranked candidate POIs associated with the category, ranking the candidate POIs using the scaled scores, for the candidate POIs that are associated with the one or more categories, and the non-scaled scores, for the candidate POIs that are not associated with the one or more categories, and providing data that identifies two or more of the candidate POIs, as ranked according to the scaled scores and the non-scaled scores.

Enforcing category diversity

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for enforcing category diversity of points of interest (POIs). In one aspect, a method includes receiving a request to identify POIs, obtaining data identifying (i) POIs that satisfy the request, (ii) a category associated with each POI, and (iii) a non-scaled score associated with each POI, and ranking, for each category, the POIs based on the non-scaled scores. The method also includes scaling, for each of one or more categories, the non-scaled scores of the ranked POIs associated with the category, ranking the POIs using the scaled scores, for the POIs that are associated with the one or more categories, and the non-scaled scores, for the POIs that are not associated with the one or more categories, and providing data that identifies the POIs, as ranked according to the scaled and the non-scaled scores.

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San Carlos, CA, United States of America

Neha Arora