Reverse top-k group nearest neighbor search

Authors:
Tao Jiang;Yunjun Gao;Bin Zhang;Qing Liu;Lu Chen
Affiliations:
College of Mathematics Physics and Information Engineering, Jiaxing University, Jiaxing, China;College of Computer Science, Zhejiang University, Hangzhou, China;College of Mathematics Physics and Information Engineering, Jiaxing University, Jiaxing, China;College of Computer Science, Zhejiang University, Hangzhou, China;College of Computer Science, Zhejiang University, Hangzhou, China
Venue:
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
Year:
2013

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Abstract

This paper identifies and solves a novel query, namely, R everse Top-k G roup N earest N eighbor (RkGNN) query. Given a data set P, a query object q, and two (user specified) parameters m and k, an RkGNN query finds k subsets, which have the least aggregate distances, such that each subset contains m data objects from P and has q in its group nearest neighbor. We formalize the RkGNN query. Then, we propose several algorithms for efficiently processing RkGNN queries. Our methods employ some effective pruning heuristics to prune away unqualified candidate subsets, utilize the sorting andthreshold mechanisms to shrink the search space, and make use of the advantages of lazy and spatial pruning techniques. Extensive experiments with both real and synthetic datasets demonstrate the performance of the proposed algorithms in terms of effectiveness and efficiency.