Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-12026-8_16
Title: Answering top-fc similar region queries
Authors: Sheng, C.
Zheng, Y.
Hsu, W. 
Lee, M.L. 
Xie, X.
Issue Date: 2010
Citation: Sheng, C.,Zheng, Y.,Hsu, W.,Lee, M.L.,Xie, X. (2010). Answering top-fc similar region queries. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5981 LNCS (PART 1) : 186-201. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-12026-8_16
Abstract: Advances in web technology have given rise to new information retrieval applications. In this paper, we present a model for geographical region search and call this class of query similar region query. Given a spatial map and a query region, a similar region search aims to find the top-fc most similar regions to the query region on the spatial map. We design a quadtree based algorithm to access the spatial map at different resolution levels. The proposed search technique utilizes a filter-and-refine manner to prune regions that are not likely to be part of the top-fc results, and refine the remaining regions. Experimental study based on a real world dataset verifies the effectiveness of the proposed region similarity measure and the efficiency of the algorithm. © Springer-Verlag Berlin Heidelberg 2010.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/40945
ISBN: 3642120253
ISSN: 03029743
DOI: 10.1007/978-3-642-12026-8_16
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