Title :
Web cartography for online site promotion: an algorithm for clustering Web resources
Author :
Velin, François ; Kuntz, Pascale ; Briand, Henri
Abstract :
Presents a Web cartography approach 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 analyses 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
Keywords :
business graphics; data mining; data visualisation; graphs; hypermedia; information resources; iterative methods; marketing data processing; matrix decomposition; pattern clustering; Cognac; Laplacian matrix; Web cartography; World Wide Web resource clustering algorithm; candidate sites; computer-aided design; corpus; geometric space; graph analyses; hyperlink creation; iterative approach; link network; maps; online site promotion; semantic analyses; site graph partitioning problem; spectral decomposition; strongly connected sites; targeted visitor flow; text data; Application software; Clustering algorithms; Data mining; Design automation; Iterative methods; Laplace equations; Matrix decomposition; Navigation; Search engines; Stress;
Conference_Titel :
Data Mining, 2001. ICDM 2001, Proceedings IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
0-7695-1119-8
DOI :
10.1109/ICDM.2001.989561