Constructing multi-granular and topic-focused web site maps

Site maps are essential to assist users in navigating a Web site. Most of the site maps are constructed manually and are static. However, di erent users may have di erent preferences and purposes for using a Web site. For example, a user may want to see a more detailed map while another user prefers a more abstract map. Two users looking for di erent topics at a large portal site would bene t more from two site maps with di erent focuses than a single map. In this paper, we present a technique for automatically constructing multi-granular and topic-focused site maps by utilizing directory paths, page contents, and link structures. In these site maps, the Web site topology is preserved and document importance, indicated by citation and semantic relevancy to user's topics of interest, is used for prioritizing the presentation of pages and directories. Experiments on real Web data have been conducted to validate the usefulness of the technique.

[1]  Israel Ben-Shaul,et al.  WebCutter: A System for Dynamic and Tailorable Site Mapping , 1997, Comput. Networks.

[2]  Mary Czerwinski,et al.  From latent semantics to spatial hypertext—an integrated approach , 1998, HYPERTEXT '98.

[3]  Chaomei Chen Structuring and visualising the WWW by generalised similarity analysis , 1997, HYPERTEXT '97.

[4]  Andrei Z. Broder,et al.  The Connectivity Server: Fast Access to Linkage Information on the Web , 1998, Comput. Networks.

[5]  Sougata Mukherjea,et al.  Focus+context views of World-Wide Web nodes , 1997, HYPERTEXT '97.

[6]  Wen-Syan Li,et al.  Defining logical domains in a web site , 2000, HYPERTEXT '00.

[7]  Lawrence Davis,et al.  A Hybrid Genetic Algorithm for Classification , 1991, IJCAI.

[8]  Loren G. Terveen,et al.  Finding and visualizing inter-site clan graphs , 1998, CHI.

[9]  Sougata Mukherjea,et al.  WTMS: a system for collecting and analyzing topic-specific Web information , 2000, Comput. Networks.

[10]  Alberto Maria Segre,et al.  Programs for Machine Learning , 1994 .

[11]  George G. Robertson,et al.  The WebBook and the Web Forager: an information workspace for the World-Wide Web , 1996, CHI.

[12]  Ravi Kumar,et al.  Trawling the Web for Emerging Cyber-Communities , 1999, Comput. Networks.

[13]  David G. Durand,et al.  MAPA: a system for inducing and visualizing hierarchy in Websites , 1998, HYPERTEXT '98.

[14]  Pat Langley,et al.  Selection of Relevant Features and Examples in Machine Learning , 1997, Artif. Intell..