The Open UniversitySkip to content

Mining a web citation database for document clustering

He, Y.; Hui, S. C. and Fong, A. C. M. (2002). Mining a web citation database for document clustering. Applied Artificial Intelligence, 16(4) pp. 283–302.

DOI (Digital Object Identifier) Link:
Google Scholar: Look up in Google Scholar


The World Wide Web has become an important medium for disseminating scientific publications. Many publications are now made available over the Web. However, existing search engines are ineffective in searching these publications, as they do not index Web publications that normally appear in PDF (Portable Document Format) or PostScript formats. One way to index Web publications is through citation indices, which contain the references that the publications cite. Web Citation Database is a data warehouse to store the citation indices. In this paper, we propose a mining process to extract document cluster knowledge from the Web Citation Database to support the retrieval of Web publications. The mining techniques used for document cluster generation are based on Kohonen's Self-Organizing Map (KSOM) and Fuzzy Adaptive Resonance Theory (Fuzzy ART). The proposed techniques have been incorporated into a citation-based retrieval system known as PubSearch for Web scientific publications.

Item Type: Journal Item
Copyright Holders: 2002 Taylor & Francis
ISSN: 1087-6545
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 28566
Depositing User: Kay Dave
Date Deposited: 20 Apr 2011 13:40
Last Modified: 07 Dec 2018 09:53
Share this page:


Altmetrics from Altmetric

Citations from Dimensions

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU