A comparable study employing weka clustering/classification algorithms for web page classification
dc.creator | Charalampopoulos, I. | en |
dc.creator | Anagnostopoulos, I. | en |
dc.date.accessioned | 2015-11-23T10:24:28Z | |
dc.date.available | 2015-11-23T10:24:28Z | |
dc.date.issued | 2011 | |
dc.identifier | 10.1109/PCI.2011.52 | |
dc.identifier.isbn | 9780769543895 | |
dc.identifier.uri | http://hdl.handle.net/11615/26572 | |
dc.description.abstract | Documents 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.uri | http://www.scopus.com/inward/record.url?eid=2-s2.0-81455132842&partnerID=40&md5=52db1dc0af28338fb1758f5c230db368 | |
dc.subject | Classification | en |
dc.subject | Clustering | en |
dc.subject | WEKA | en |
dc.subject | Classification methods | en |
dc.subject | Method evaluation | en |
dc.subject | Testing results | en |
dc.subject | Web classification | en |
dc.subject | Web content | en |
dc.subject | Web page classification | en |
dc.subject | Algorithms | en |
dc.subject | Classification (of information) | en |
dc.subject | Information science | en |
dc.subject | Interfaces (computer) | en |
dc.subject | Information retrieval systems | en |
dc.title | A comparable study employing weka clustering/classification algorithms for web page classification | en |
dc.type | conferenceItem | en |
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