Section: New Results

Keywords : unsupervised clustering, Web Usage Mining, dynamic clustering algorithm.

Block clustering and Web Content Data Mining

Participants : Malika Charrad, Yves Lechevallier.

Our aim is to analyze textual data of a web site. Our approach [40] consists of three steps: Web pages classification, preprocessing of web pages content and block clustering. The first step consists in classifying web site pages into to major categories: auxiliary pages and content pages. In the second step, web pages content is preprocessed in order to select descriptors to represent each page in the web site. As a result, a matrix of web site pages and vectors of descriptors is constructed. In the last step, a simultaneous clustering is applied to rows and columns of this matrix to discover biclusters of pages and descriptors.