FINCH: evaluating reverse k-Nearest-Neighbor queries on location data

Authors:
Wei Wu;Fei Yang;Chee-Yong Chan;Kian-Lee Tan
Affiliations:
National University of Singapore;National University of Singapore;National University of Singapore;National University of Singapore
Venue:
Proceedings of the VLDB Endowment
Year:
2008

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Abstract

A Reverse k-Nearest-Neighbor (RkNN) query finds the objects that take the query object as one of their k nearest neighbors. In this paper we propose new solutions for evaluating RkNN queries and its variant bichromatic RkNN queries on 2-dimensional location data. We present an algorithm named INCH that can compute a RkNN query's search region (from which the query result candidates are drawn). In our RkNN evaluation algorithm called FINCH, the search region restricts the search space, and the search region is tightened each time a new result candidate is found. We also propose a method that enables us to apply any RkNN algorithm on bichromatic RkNN queries. With that, our FINCH algorithm is also used to evaluate bichromatic RkNN queries. Experiments show that our solutions are more efficient than existing algorithms.