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Web Cartography for Online State Promotion: An Algorithm for Clustering Web Resources
San Jose, California November 29-December 02
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDM.2001.989561First IEEE International Conference o ...
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This paper presents an approach of Web cartography to be used in the context of online site promotion. The overall objective is to provide users with handy maps offering information about candidate sites for the creation of hyperlinks that enable a large flow of targeted visitors. Two main types of data must be considered; texts and hyperlinks. We propose to exploit the latter to construct a relevant corpus on which semantic as well as graph analysis can be applied. The stress is put on the clustering of Web resources based on the link network, which makes it possible to highlight groups of strongly connected sites which are of the utmost interest for our application. To tackle the site graph partitioning problem, we turn to a promising iterative approach initially developed in the context of computer-aided design. It uses spectral decomposition of the Laplacian matrix to embed the considered graph in a geometric space where efficient methods can be applied. An algorithm that was adapted from an existing one implements the method. Experiments were conducted on a real application case concerning the promotion of a site dealing with Cognac. We present the obtained map as well as leads to exploit it.
Citation:
Francois Velin, Pascale Kuntz, Henri Briand, "Web Cartography for Online State Promotion: An Algorithm for Clustering Web Resources," icdm, pp.529, First IEEE International Conference on Data Mining (ICDM'01), 2001
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