Abstract: Aspect of the subject technology relate to a computer-implemented method for identifying geographic features related to a location lookup point. In some implementations, the method includes steps for receiving location information for a location look-up point, generating a plurality of search cells containing the location look-up point, wherein the plurality of search cells correspond with a respective plurality of hierarchical map cells and using the plurality of search cells to identify at least one geographic feature that is associated with at least one of the plurality of search cells. In certain aspects, the method can further include steps for providing at least one geographic feature to a user for display. Systems and computer-readable media for generating a geographic feature index are also provided.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for receiving a search query originating from a user device, the search query including a geographic feature name; receiving data identifying one or more candidate point-of-interests, each candidate point-of-interest comprising data that identifies a corresponding candidate geographic entity, each candidate point-of-interest having an initial relevance score; generating one or more biasing boxes, wherein each biasing box defines a geographic region, and each biasing box is defined based on location information associated with the user device or a user using the user device; using the biasing boxes to generate respective adjusted relevance scores for the candidate point-of-interests; selecting a point-of-interest from the one or more candidate point-of-interests according to the respective adjusted relevance scores of the candidate point-of-interests; and using the selected point-of-interest to identify a location r

Abstract: Methods, systems, and implementations are disclosed to schedule a plurality of tasks on one or more processors. The tasks may be part of a larger job based on a user initiated query for information retrieval. One example method of operation may include estimating, based upon historical actual execution times of tasks of a respective corresponding type, an expected execution time for each task of the plurality of tasks. The method may further include scheduling the plurality of tasks for execution on the one or more processors based upon the estimated expected execution time of each task. The scheduling procedure utilized ultimately produces an optimized task execution schedule, and in turn, minimizes the expected job completion time.