Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-12026-8_16
DC FieldValue
dc.titleAnswering top-fc similar region queries
dc.contributor.authorSheng, C.
dc.contributor.authorZheng, Y.
dc.contributor.authorHsu, W.
dc.contributor.authorLee, M.L.
dc.contributor.authorXie, X.
dc.date.accessioned2013-07-04T08:16:01Z
dc.date.available2013-07-04T08:16:01Z
dc.date.issued2010
dc.identifier.citationSheng, 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. <a href="https://doi.org/10.1007/978-3-642-12026-8_16" target="_blank">https://doi.org/10.1007/978-3-642-12026-8_16</a>
dc.identifier.isbn3642120253
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40945
dc.description.abstractAdvances 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.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-12026-8_16
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1007/978-3-642-12026-8_16
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume5981 LNCS
dc.description.issuePART 1
dc.description.page186-201
dc.identifier.isiutNOT_IN_WOS
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