Mapquest, Inc.

Andrew McMahon

Antony Pegg

Miria Grunick

Darren A Spehr

Thomas P Vaccarino

Brian J McMahon

Systems and methods are disclosed for partitioning data into n partitions in a database used for information retrieval. According to certain embodiments implemented with at least one processor, a perceived load is determined for each of a plurality of substrings, each of the substrings corresponding to one or more entries in the database. The plurality of substrings are ordered from highest to lowest perceived load. Data associated with each of the first n substrings is assigned to a separate partition, wherein n is greater than one. Moreover, data associated with each of the remaining substrings is assigned to the n partitions based on a score. The score is computed by calculating, for each partition, a load variance and an entropy weight for the candidate substring. The load variance and the entropy weight are combined, and the candidate substring is assigned to the partition that has the lowest combined score.

Computerized systems and methods for partitioning data for information retrieval

Systems and methods are disclosed for identifying points-of-interest using customized query prediction. According to certain embodiments, a partial query is received from a client via a network. The partial query may comprise a plurality of characters associated with a full query and location data associated with the client. The received partial query may be analyzed using at least one dictionary. Based on the analysis of the received partial query, at least one query may be predicted. Moreover, at least one point-of-interest may be identified based on the at least one predicted query. Further, data associated with the at least one identified point-of-interest may be transmitted over the network to the client prior to receiving the full query from the client.

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Washington, DC, United States of America

Andrew McMahon