A Clustering Application for the Web Usage Mining

dc.contributor.authorKouici, Salima
dc.date.accessioned2013-11-28T13:06:01Z
dc.date.available2013-11-28T13:06:01Z
dc.date.issued2012-12
dc.description.abstractThe Web Usage Mining constitutes a new branch of the Web Mining. It allows the study of the behavior of both users and potential customers via their site navigation. The mainly used source for the Web Usage Mining is the servers Log Files. A Log File contains an important mass of data, including user’s information (username, used software, etc.) and all the queries he has made on the website (requested files, the number of bytes transferred, time spent on each page, the page of entry to the site .... etc.). In this work we shall outline an application, made on this type of data, which is based on a clustering method, namely KMEANS. This application allows the definition of homogeneous groups constituting users profiles so that to anticipate the needs and with a view of communication adapted to each segment of users. In this application we have recorded some technical problems. These problems concerns the data cleaning (removing queries of images and multimedia files associated with web pages, removing queries from search bots... etc.) and the setting up of visitor sessions, knowing that a session is a sequence of pages viewed by the same user.fr_FR
dc.identifier.isrnCERIST-DRDSI/RR--12-000000038--dzfr_FR
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/401
dc.publisherCERIST
dc.relation.ispartofRapports de recherche internes
dc.relation.ispartofseriesRapports de recherche internes
dc.relation.placeAlger
dc.subjectClusteringfr_FR
dc.subjectK-Meansfr_FR
dc.subjectWeb Usage Miningfr_FR
dc.subjectServer Log Filefr_FR
dc.titleA Clustering Application for the Web Usage Miningfr_FR
dc.typeTechnical Report
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