Rough fuzzy approach for web usage mining

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dc.contributor.authorSiriporn Chimphlee
dc.contributor.authorNaomie Salim
dc.contributor.authorMohd Salihin Bin Ngadiman
dc.contributor.authorWitcha Chimphlee
dc.contributor.authorSurat Srinoy
dc.contributor.correspondenceS. Chimphlee; Faculty of Science and Technology, Suan Dusit Rajabhat University, Dusit, Bangkok, 295 Rajasrima Rd, Thailand; email: siriporn_chi@dusit.ac.th
dc.date.accessioned2025-03-10T07:38:08Z
dc.date.available2025-03-10T07:38:08Z
dc.date.issued2006
dc.description.abstractWeb usage mining is a new subfield of data mining research. It aims at discovery of trends and regularities in web users' access patterns. In the past few years, web usage mining techniques have grown rapidly together with the explosive growth of the web, both in the research and commercial areas. A challenge in web classification is how to deal with the high dimensionality of the feature space. This paper applies the concept of rough fuzzy approach for classification in web usage mining tasks after we present Independent Component Analysis (ICA) for feature. Clustering is an important part of web mining that involves finding natural groupings of web resources or web users.
dc.identifier.citationWSEAS Transactions on Information Science and Applications
dc.identifier.issn17900832
dc.identifier.scopus2-s2.0-33645139674
dc.identifier.urihttps://repository.dusit.ac.th//handle/123456789/5074
dc.languageEnglish
dc.rights.holderScopus
dc.subjectIndependent component analysis
dc.subjectRough fuzzy
dc.subjectWeb log mining
dc.subjectWeb usage mining
dc.titleRough fuzzy approach for web usage mining
dc.typeArticle
mods.location.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-33645139674&partnerID=40&md5=9f24431df9c60d09b4ed6d98cfd63229
oaire.citation.endPage621
oaire.citation.issue3
oaire.citation.startPage618
oaire.citation.volume3
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