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Article Dans Une Revue IADIS International Journal on www/Internet Année : 2007

Clustering Web Pages Sequences With Artificial Ants

Résumé

This paper introduces new Web usage mining tools designed to help characterizing user accesses on websites. Our approach relies on a categorization of Web user sessions to help identifying and understanding major trends in the navigations. The novelty of our work mainly relies in the clustering method that is a fast unsupervised ant-inspired clustering algorithm paired with new similarity measures that handle sessions either as a sequence or an unordered set of Web pages. Our algorithm is evaluated on real Web log files of a French museum that contains more than 39000 user sessions over one month and a half. Our experiments show that our algorithm can build meaningful sessions clusters that can help infer Web users' motivations.
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Dates et versions

hal-01172648 , version 1 (07-07-2015)

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  • HAL Id : hal-01172648 , version 1

Citer

Nicolas Labroche. Clustering Web Pages Sequences With Artificial Ants. IADIS International Journal on www/Internet, 2007, 5 (1), pp.503-510. ⟨hal-01172648⟩
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