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|Title:||Answering top-fc similar region queries||Authors:||Sheng, C.
|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|
|Appears in Collections:||Staff Publications|
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