Using a new relational concept to improve the clustering performance of search engines

被引：7
|
作者：
Chen, Lin-Chih [1 ]
机构：
[1] Natl Dong Hwa Univ, Dept Informat Management, Shoufeng 97401, Hualien, Taiwan
来源：
INFORMATION PROCESSING & MANAGEMENT | 2011年 / 47卷 / 02期
关键词：
Document clustering; Semantic relation; Relational concept; Web search engines; Web documents; RETRIEVAL;
D O I：
10.1016/j.ipm.2010.04.001
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码：287 / 299
页数：13
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