Web site improvements based on representative pages identification

Ríos S.A.; Yasuda, H.; Aoki, T; Velásquez J.D.

Keywords: behavior, maps, structures, identification, sites, data, self, mining, real, content, browsing, retrieval, web, websites, problem, solving, based, browsers, organizing, Pages, Representative

Abstract

Many researchers have successfully shown that web content mining technics and web usage mining techniques can help to find out important patterns on the content and browsing behavior in a site. However, still it is an open problem how to reach a good interpretation of the cluster results after the mining process. We propose a technique called Reverse Clustering Analysis (RCA) applied to a Self Organizing Feature Map in order to identify the most representative Web Pages of the Site. Then use this information to perform enhancements in the site. Our mining process is based on the combination of WCM and WUM to find out the content that is most interesting for the visitors. We successfully test our proposal in a real web site. © Springer-Verlag Berlin Heidelberg 2005.

Más información

Título de la Revista: COMPUTATIONAL LOGISTICS (ICCL 2021)
Volumen: 3809
Editorial: SPRINGER INTERNATIONAL PUBLISHING AG
Fecha de publicación: 2005
Página de inicio: 1162
Página final: 1166
URL: http://www.scopus.com/inward/record.url?eid=2-s2.0-33745584815&partnerID=q2rCbXpz