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Book Chapter: Processing Constrained K-Closest Pairs Queries in Crime Databases

TitleProcessing Constrained K-Closest Pairs Queries in Crime Databases
Authors
KeywordsSpatial analysis
Crime databases
Constrained closest pairs
Query processing
R-tree
Issue Date2010
AbstractRecently, spatial analysis in crime databases has attracted increased attention. In order to cope with the problem of discovering the closest pairs of objects within a constrained spatial region, as required in crime investigation applications, we propose a query processing algorithm called Growing Window based Constrained k-Closest Pairs (GWCCP). The algorithm incrementally extends the query window without searching the whole workspace for multiple types of spatial objects. We use an optimized R-tree to store the index entities and employ a density-based range estimation approach to approximate the query range. We introduce a distance threshold with regard to the closest pair of objects to prune tree nodes in order to improve query performance. Experiments discuss the effect of three important factors, i.e., the portion of overlapping between the workspaces of two data sets, the value of k, and the buffer size. The results show that GWCCP outperforms the heap-based approach as a baseline in a number of aspects. In addition, GWCCP performs better within the same data set in terms of time and space efficiency.
DescriptionThis book is volume 9 under the series of Annals of Information Systems. An earlier version of the paper received the best paper award at the IEEE International Conference on Intelligence and Security Informatics 2008 with DOI link http://dx.doi.org/10.1109/ISI.2008.4565030
Persistent Identifierhttp://hdl.handle.net/10722/125585
ISBN

 

DC FieldValueLanguage
dc.contributor.authorQiao, Sen_HK
dc.contributor.authorTang, Cen_HK
dc.contributor.authorJin, Hen_HK
dc.contributor.authorDai, Sen_HK
dc.contributor.authorChen, Xen_HK
dc.contributor.authorChau, Men_HK
dc.contributor.authorHu, Jen_HK
dc.date.accessioned2010-10-31T11:39:50Z-
dc.date.available2010-10-31T11:39:50Z-
dc.date.issued2010en_HK
dc.identifier.isbn9781441913241-
dc.identifier.urihttp://hdl.handle.net/10722/125585-
dc.descriptionThis book is volume 9 under the series of Annals of Information Systems. An earlier version of the paper received the best paper award at the IEEE International Conference on Intelligence and Security Informatics 2008 with DOI link http://dx.doi.org/10.1109/ISI.2008.4565030-
dc.description.abstractRecently, spatial analysis in crime databases has attracted increased attention. In order to cope with the problem of discovering the closest pairs of objects within a constrained spatial region, as required in crime investigation applications, we propose a query processing algorithm called Growing Window based Constrained k-Closest Pairs (GWCCP). The algorithm incrementally extends the query window without searching the whole workspace for multiple types of spatial objects. We use an optimized R-tree to store the index entities and employ a density-based range estimation approach to approximate the query range. We introduce a distance threshold with regard to the closest pair of objects to prune tree nodes in order to improve query performance. Experiments discuss the effect of three important factors, i.e., the portion of overlapping between the workspaces of two data sets, the value of k, and the buffer size. The results show that GWCCP outperforms the heap-based approach as a baseline in a number of aspects. In addition, GWCCP performs better within the same data set in terms of time and space efficiency.-
dc.languageengen_HK
dc.subjectSpatial analysis-
dc.subjectCrime databases-
dc.subjectConstrained closest pairs-
dc.subjectQuery processing-
dc.subjectR-tree-
dc.titleProcessing Constrained K-Closest Pairs Queries in Crime Databasesen_HK
dc.typeBook_Chapteren_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=9781441913241&volume=&spage=59&epage=75&date=2010&atitle=Processing+Constrained+K-Closest+Pairs+Queries+in+Crime+Databases-
dc.identifier.emailChau, M: mchau@business.hku.hken_HK
dc.identifier.authorityChau, MCL=rp01051en_HK
dc.identifier.doi10.1007/978-1-4419-1325-8_4-
dc.identifier.hkuros172936en_HK
dc.identifier.spage59en_HK
dc.identifier.epage75en_HK

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