Asian Journal of Information Technology
ISSN: Online 1993-5994ISSN: Print 1682-3915
Abstract
Clustering Web documents is a fundamental task in Web Mining. Clustering analysis assists in reducing search space and decreasing information retrieval time. In this study we present a new data model for Web document representation based on granulation computing, named as Expanded Vector Space Model (EVSM), which facilitates knowledge engineers to acquire and understand processing results. We experimentally evaluate the proposed approach and demonstrate that our algorithm is promising and efficient.
How to cite this article:
1Faliang Huang and Shichao Zhang . Web Document Representation Based on Knowledge Granularity.
DOI: https://doi.org/10.36478/ajit.2006.79.85
URL: https://www.makhillpublications.co/view-article/1682-3915/ajit.2006.79.85