Web Mining for Identifying Research Trends

Tho, Q. T., Hui, S. C. and Fong, A. (2003) Web Mining for Identifying Research Trends. In: 6th International Conference on Asian Digital Libraries (ICADL), Kuala Lumpur, Malaysia, 8-12 Dec 2003, pp. 290-301. ISBN 9783540245940 (doi: 10.1007/978-3-540-24594-0_28)

Abstract

This paper proposes a web mining approach for identifying research trends. The proposed approach comprises a number of data mining techniques. To perform web mining, the Indexing Agents search and download scientific publications from web sites that typically include academic web pages, then they extract citations and store them in a Web Citation Database. The Temporal Document Clustering technique and Journal Co-Citation Clustering technique are applied to the Web Citation Database to generate temporal document clusters and journal clusters respectively. The Multi-Clustering technique is then proposed to mine the document and journal clusters for their inter-relationships. Finally, the knowledge that is mined from the inter-relationships is used for the detection of trends and emergent trends for a specified research area. In this paper, we will discuss the proposed web mining approach, and the performance of the proposed approach.

• Item Type: Conference Proceedings
• Additional Information: Lecture notes in computer science: 2911
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Fong, Dr Alvis Cheuk Min
• Authors: Tho, Q. T., Hui, S. C., and Fong, A.
• College/School: College of Science and Engineering > School of Computing Science
• ISSN: 0302-9743
• ISBN: 9783540245940