Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
515684 | Information Processing & Management | 2011 | 13 Pages |
Abstract
In this paper, we present a novel clustering algorithm to generate a number of candidate clusters from other web search results. The candidate clusters generate a connective relation among the clusters and the relation is semantic. Moreover, the algorithm also contains the following attractive properties: (1) it can be applied to multilingual web documents, (2) it improves the clustering performance of any search engine, (3) its unsupervised learning can automatically identify potentially relevant knowledge without using any corpus, and (4) clustering results are generated on the fly and fitted into search engines.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Lin-Chih Chen,