Exploiting Knowledge Representation for Pattern Interpretation

Web Usage Mining (WUM) is the application of data mining techniques over web server logs in order to extract navigation usage patterns. Semantic Web Usage Mining aims at combining the Semantic Web and WUM. The main goal of the Semantic WUM is to improve the process and the results of WUM by exploiting the new semantic structure in the Web. Pattern analysis is a critical phase in WUM, for two main reasons: a) mining algorithms yield a huge number of patterns; b) there is a significant semantic gap between URLs and events performed by users. This paper discusses the use of ontologies available at Semantic Web to support the interpretation of web usage sequential patterns. Functionality is targeted at supporting the comprehension of patterns, as well as on the identification of potentially interesting ones through interactive pattern rummaging.

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