Title

On Discovering Concept Entities from Web Sites

Publication Type

Conference Proceeding Article

Publication Date

5-2005

Abstract

A web site usually contains a large number of concept entities, each consisting of one or more web pages connected by hyperlinks. In order to discover these concept entities for more expressive web site queries and other applications, the web unit mining problem has been proposed. Web unit mining aims to determine web pages that constitute a concept entity and classify concept entities into categories. Nevertheless, the performance of an existing web unit mining algorithm, iWUM, suffers as it may create more than one web unit (incomplete web units) from a single concept entity. This paper presents a new web unit mining algorithm, kWUM, which incorporates site-specific knowledge to discover and handle incomplete web units by merging them together and assigning correct labels. Experiments show that the overall accuracy has been significantly improved.

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Research Areas

Data Management and Analytics

Publication

Computational Science and Its Applications – ICCSA 2005: International Conference, Singapore, May 9-12, 2005, Proceedings, Part II

Volume

3481

First Page

1177

Last Page

1186

ISBN

9783540320449

Identifier

10.1007/11424826_125

Publisher

Springer Verlag

City or Country

Singapore

Additional URL

http://dx.doi.org/10.1007/11424826_125