An efficient algorithm for arbitrary reverse furthest neighbor queries

Authors:
Jianquan Liu;Hanxiong Chen;Kazutaka Furuse;Hiroyuki Kitagawa
Affiliations:
Department of Computer Science, Graduate School of SIE, University of Tsukuba, Tsukuba, Ibaraki, Japan;Department of Computer Science, Graduate School of SIE, University of Tsukuba, Tsukuba, Ibaraki, Japan;Department of Computer Science, Graduate School of SIE, University of Tsukuba, Tsukuba, Ibaraki, Japan;Department of Computer Science, Graduate School of SIE, University of Tsukuba, Tsukuba, Ibaraki, Japan and Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
Venue:
APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
Year:
2012

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Abstract

Given an object set O and a query object q, the reverse furthest neighbor (RFN) query retrieves the objects in O, whose furthest neighbor is q. In this paper, we consider the arbitrary RFN query that is without constraint of its location. The state-of-the-art method is not efficient for such kind of queries. Therefore, we address this problem by introducing our new findings on the filtering techniques. Firstly, we show the evidence that exhibits the inefficiency of the state-of-the-art method. We then figure out a non-trivial safe area to guarantee the efficiency for query processing, even meeting the ideal efficiency. We also design an efficient algorithm to answer the RFN query without any cost of filtering or refinement, when q is located in such safe area. Extensive experiments on both synthetic and real datasets are conducted to evaluate the effectiveness, efficiency and scalability of our algorithm. The results sufficiently indicate that our algorithm significantly outperforms the competitive ones in all the aspects.