Please use this identifier to cite or link to this item: https://doi.org/10.1145/1645953.1646101
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dc.titleFast and effective histogram construction
dc.contributor.authorHalim, F.
dc.contributor.authorKarras, P.
dc.contributor.authorYap, R.H.C.
dc.date.accessioned2013-07-04T08:10:30Z
dc.date.available2013-07-04T08:10:30Z
dc.date.issued2009
dc.identifier.citationHalim, F., Karras, P., Yap, R.H.C. (2009). Fast and effective histogram construction. International Conference on Information and Knowledge Management, Proceedings : 1167-1176. ScholarBank@NUS Repository. https://doi.org/10.1145/1645953.1646101
dc.identifier.isbn9781605585123
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40707
dc.description.abstractHistogram construction or sequence segmentation is a basic task with applications in database systems, information retrieval, and knowledge management. Its aim is to approximate a sequence by line segments. Unfortunately, the quadratic algorithm that derives an optimal histogram for Euclidean error lacks the desired scalability. Therefore, sophisticated approximation algorithms have been recently proposed, while several simple heuristics are used in practice. Still, these solutions fail to resolve the efficiency-quality tradeoff in a satisfactory manner. In this paper we take a fresh view on the problem. We propose conceptually clear and scalable algorithms that efficiently derive high-quality histograms. We experimentally demonstrate that existing approximation schemes fail to deliver the desired efficiency and conventional heuristics do not fare well on the side of quality. On the other hand, our schemes match or exceed the quality of the former and the efficiency of the latter. Copyright 2009 ACM.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1145/1645953.1646101
dc.sourceScopus
dc.subjectEfficiency
dc.subjectHistograms
dc.subjectSegmentation
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1145/1645953.1646101
dc.description.sourcetitleInternational Conference on Information and Knowledge Management, Proceedings
dc.description.page1167-1176
dc.identifier.isiutNOT_IN_WOS
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