Title

Web Unit Mining: Finding and Classifying Subgraphs of Web Pages

Publication Type

Conference Proceeding Article

Publication Date

11-2003

Abstract

In web classification, most researchers assume that the objects to classify are individual web pages from one or more web sites. In practice, the assumption is too restrictive since a web page itself may not always correspond to a concept instance of some semantic concept (or category) given to the classification task. In this paper, we want to relax this assumption and allow a concept instance to be represented by a subgraph of web pages or a set of web pages. We identify several new issues to be addressed when the assumption is removed, and formulate the web unit mining problem. We also propose an iterative web unit mining (iWUM) method that first finds subgraphs of web pages using some knowledge about web site structure. From these web subgraphs, web units are constructed and classified into semantic concepts (or categories) in an iterative manner. Our experiments using the WebKB dataset showed that iWUM improves the overall classification performance and works very well on the more structured parts of a web site.

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Research Areas

Data Management and Analytics

Publication

CIKM '03: Proceedings of the 12th international conference on Information and knowledge management

First Page

108

Last Page

115

ISBN

9781581137231

Identifier

10.1145/956863.956885

Publisher

ACM

City or Country

New Orleans, LA

Additional URL

http://dx.doi.org/10.1145/956863.956885