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Conference Paper: Uncertain data mining: An example in clustering location data

TitleUncertain data mining: An example in clustering location data
Authors
KeywordsAlgorithms
Computer science
Information retrieval
Pattern recognition
Clustering
Issue Date2006
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006), Singapore, 9-12 April 2006. In Lecture Notes In Computer Science, 2006, v. 3918, p. 199-204 How to Cite?
AbstractData uncertainty is an inherent property in various applications due to reasons such as outdated sources or imprecise measurement. When data mining techniques are applied to these data, their uncertainty has to be considered to obtain high quality results. We present UK-means clustering, an algorithm that enhances the K-means algorithm to handle data uncertainty. We apply UK-means to the particular pattern of moving-object uncertainty. Experimental results show that by considering uncertainty, a clustering algorithm can produce more accurate results. © Springer-Verlag Berlin Heidelberg 2006.
DescriptionLNCS v. 3918 has title: Advances in knowledge discovery and data mining: 10th Pacific-Asia Conference, PAKDD 2006, Singapore, April 9-12, 2006, proceedings
Persistent Identifierhttp://hdl.handle.net/10722/129579
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
References

 

DC FieldValueLanguage
dc.contributor.authorChau, Men_HK
dc.contributor.authorCheng, Ren_HK
dc.contributor.authorKao, Ben_HK
dc.contributor.authorNg, Jen_HK
dc.date.accessioned2010-12-23T08:39:26Z-
dc.date.available2010-12-23T08:39:26Z-
dc.date.issued2006en_HK
dc.identifier.citationThe 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006), Singapore, 9-12 April 2006. In Lecture Notes In Computer Science, 2006, v. 3918, p. 199-204en_HK
dc.identifier.issn0302-9743en_HK
dc.identifier.urihttp://hdl.handle.net/10722/129579-
dc.descriptionLNCS v. 3918 has title: Advances in knowledge discovery and data mining: 10th Pacific-Asia Conference, PAKDD 2006, Singapore, April 9-12, 2006, proceedings-
dc.description.abstractData uncertainty is an inherent property in various applications due to reasons such as outdated sources or imprecise measurement. When data mining techniques are applied to these data, their uncertainty has to be considered to obtain high quality results. We present UK-means clustering, an algorithm that enhances the K-means algorithm to handle data uncertainty. We apply UK-means to the particular pattern of moving-object uncertainty. Experimental results show that by considering uncertainty, a clustering algorithm can produce more accurate results. © Springer-Verlag Berlin Heidelberg 2006.en_HK
dc.languageengen_US
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_HK
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_HK
dc.rightsThe original publication is available at www.springerlink.com-
dc.subjectAlgorithms-
dc.subjectComputer science-
dc.subjectInformation retrieval-
dc.subjectPattern recognition-
dc.subjectClustering-
dc.titleUncertain data mining: An example in clustering location dataen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0302-9743&volume=3918&spage=199&epage=204&date=2006&atitle=Uncertain+data+mining:+An+example+in+clustering+location+data-
dc.identifier.emailChau, M: mchau@hkucc.hku.hken_HK
dc.identifier.emailCheng, R: ckcheng@cs.hku.hken_HK
dc.identifier.emailKao, B: kao@cs.hku.hken_HK
dc.identifier.authorityChau, M=rp01051en_HK
dc.identifier.authorityCheng, R=rp00074en_HK
dc.identifier.authorityKao, B=rp00123en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/11731139_24en_HK
dc.identifier.scopuseid_2-s2.0-33745782098en_HK
dc.identifier.hkuros176482en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33745782098&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume3918 LNAIen_HK
dc.identifier.spage199en_HK
dc.identifier.epage204en_HK
dc.publisher.placeGermanyen_HK
dc.description.otherThe 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006), Singapore, 9-12 April 2006. In Lecture Notes In Computer Science, 2006, v. 3918, p. 199-204-
dc.identifier.scopusauthoridChau, M=7006073763en_HK
dc.identifier.scopusauthoridCheng, R=7201955416en_HK
dc.identifier.scopusauthoridKao, B=35221592600en_HK
dc.identifier.scopusauthoridNg, J=14034661100en_HK

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