Please use this identifier to cite or link to this item:
|Title:||FINCH: Evaluating reverse k-Nearest-Neighbor queries on location data||Authors:||Wu, W.
|Issue Date:||2008||Citation:||Wu, W.,Yang, F.,Chan, C.,Tan, K. (2008). FINCH: Evaluating reverse k-Nearest-Neighbor queries on location data. Proceedings of the VLDB Endowment 1 (1) : 1056-1067. ScholarBank@NUS Repository.||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. © 2008 VLDB Endowment.||Source Title:||Proceedings of the VLDB Endowment||URI:||http://scholarbank.nus.edu.sg/handle/10635/39757||ISSN:||21508097|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Apr 19, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.