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Enhancing Document Clustering using Important Term of Cluster and Wikipedia  

Park, Sun (Institute Research of Information Science and Engineering, Mokpo National University)
Lee, Yeon-Woo (Department of Information Communication Engineering, Mokpo National University)
Jeong, Min-A (Department of Computer Engineering, Mokpo National University)
Lee, Seong-Ro (Department of Information Electronic Engineering, Mokpo National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.49, no.2, 2012 , pp. 45-52 More about this Journal
Abstract
This paper proposes a new enhancing document clustering method using the important terms of cluster and the wikipedia. The proposed method can well represent the concept of cluster topics by means of selecting the important terms in cluster by the semantic features of NMF. It can solve the problem of "bags of words" to be not considered the meaningful relationships between documents and clusters, which expands the important terms of cluster by using of the synonyms of wikipedia. Also, it can improve the quality of document clustering which uses the expanded cluster important terms to refine the initial cluster by re-clustering. The experimental results demonstrate that the proposed method achieves better performance than other document clustering methods.
Keywords
document clustering; NMF, non-negative matrix factorization; semantic features; wikipedia; synonym; important term;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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