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A comparable study employing weka clustering/classification algorithms for web page classification

dc.creatorCharalampopoulos, I.en
dc.creatorAnagnostopoulos, I.en
dc.date.accessioned2015-11-23T10:24:28Z
dc.date.available2015-11-23T10:24:28Z
dc.date.issued2011
dc.identifier10.1109/PCI.2011.52
dc.identifier.isbn9780769543895
dc.identifier.urihttp://hdl.handle.net/11615/26572
dc.description.abstractDocuments and web pages share many similarities. Thus classification methods used in documents can be applied to advanced web content, with or even without modifications. Algorithms for document and web classification are presented as an introduction. One out of many tools that can be used in method evaluation, application and modification is WEKA (Waikato Environment for Knowledge Analysis). Testing results and conclusions strengthen the principles and bases of classification, while demonstrating the need for a new interlayer in the evaluation of classification methods. © 2011 IEEE.en
dc.source.urihttp://www.scopus.com/inward/record.url?eid=2-s2.0-81455132842&partnerID=40&md5=52db1dc0af28338fb1758f5c230db368
dc.subjectClassificationen
dc.subjectClusteringen
dc.subjectWEKAen
dc.subjectClassification methodsen
dc.subjectMethod evaluationen
dc.subjectTesting resultsen
dc.subjectWeb classificationen
dc.subjectWeb contenten
dc.subjectWeb page classificationen
dc.subjectAlgorithmsen
dc.subjectClassification (of information)en
dc.subjectInformation scienceen
dc.subjectInterfaces (computer)en
dc.subjectInformation retrieval systemsen
dc.titleA comparable study employing weka clustering/classification algorithms for web page classificationen
dc.typeconferenceItemen


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