Google Inc.

A9.com, Inc.

Steve Martin

Daniel Alan Rodney

Diane Hernek

Yue Zhou

Haruyoshi Sakai

Benoit J Dupin

Nicholas E Matsakis

Derek Alexander Wollenstein

Dimitris Margaritis

Systems and techniques are provided for providing a scalable current leaderboard. Entries may be received. The entries may include an identifier and a score. The entries may be sorted according to a sorting criterion to obtain a leaderboard. The entries may be ranked with a rank according to the position of the entry on the leaderboard. The entry may include the rank. The leaderboard may be divided into buckets. Each bucket may include consecutive entries from the leaderboard. One of the entries may be included at the end of a first buckets and at the beginning of a second buckets. The buckets may be ordered sequentially. The bucket may be updated with score versions to produce an updated bucket, where the score versions may include new versions and old versions.

Scalable current leaderboard using delta-encoded updates

Systems, methods, and apparatus are provided for determining relevance of documents to queries. An optimized relevance function is configured to determine a relevance value of documents of a first type that are linked to documents of a second type. The relevance function is optimized to satisfy certain criteria. According to one criterion, a relevance value produced by the optimized relevance function, when invoked for documents of the first type, should have a locally maximal degree of fit to the results of the existing relevance function for the sample training documents of the second type. An assessed degree of fit of a document can be increased or decreased to arrive at an optimized relevance function that ranks the documents of the first type in a desired position relative to documents of the second type in search results. The degree of fit can be assessed by a user-provided objective function.

Ranking non-product documents

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Mountain View, CA, United States of America

Steve Martin