Title :
A Document Clustering Technique Based on Term Clustering and Association Rules
Author :
Cheng, Yuepeng ; Li, Tong ; Zhu, Song
Author_Institution :
Comput. Sci. & Eng. Dept., North China Inst. of Aerosp. Eng., Langfang, China
Abstract :
With development of internet and database technology, web mining has got more and more attentions from information science domain. This paper proposes a document clustering technique based on term clustering and association rules. In this technique, extract words from document collection firstly, then construct term clustering according to AMI(Average Mutual Information) between terms, document VSM(Vector Space Model) is represented by term clustering, and use association rules to mine document clustering. Experiment results show that performance and clustering quality of this technique are improved than those of traditional methods in the clustering process.
Keywords :
data mining; pattern clustering; vectors; word processing; Web mining; association rule; average mutual information; document clustering technique; term clustering; vector space model; word extraction; Aerospace engineering; Association rules; Clustering algorithms; Mutual information; Semantics; Variable speed drives; Web mining;
Conference_Titel :
Database Technology and Applications (DBTA), 2010 2nd International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6975-8
Electronic_ISBN :
978-1-4244-6977-2
DOI :
10.1109/DBTA.2010.5659049