dc.creatorRíos, Sebastián
dc.creatorVelásquez Silva, Juan
dc.creatorYasuda, Hiroshi
dc.creatorAoki, Terumasa
dc.date.accessioned2009-06-12T10:32:52Z
dc.date.available2009-06-12T10:32:52Z
dc.date.created2009-06-12T10:32:52Z
dc.date.issued2006
dc.identifierINTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2006, PROCEEDINGS Book Series: LECTURE NOTES IN COMPUTER SCIENCE Volume: 4224 Pages: 869-877 Published: 2006
dc.identifier0302-9743
dc.identifierhttps://repositorio.uchile.cl/handle/2250/124974
dc.description.abstractThis paper presents a conceptual based approach for improving a Web site content. Usually Web Usage Mining (WUM) techniques study the visitors' browsing behavior to obtain interesting knowledge. However, most of the work in the area leave behind the semantic information of web pages. We propose to combine the Concept-Based Knowledge Discovery in Text with the visitors sessions to perform the personalization task. This way, it is possible to obtain information about which are the users' goals when browsing a web site. Moreover, it is possible to give better browsing recomendations and help managers improving the content of their Web site. We test this idea on a real Web site to show its effectiveness.
dc.languageen
dc.publisherSPRINGER-VERLAG BERLIN
dc.subjectSYSTEMS
dc.titleConceptual classification to improve a Web site content
dc.typeArtículo de revista


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