DocumentCode :
1802476
Title :
Novelty-based Incremental Document Clustering for On-line Documents
Author :
Khy, Sophoin ; Ishikawa, Yoshiharu ; Kitagawa, Hiroyuki
Author_Institution :
University of Tsukuba, Japan
fYear :
2006
fDate :
2006
Firstpage :
40
Lastpage :
40
Abstract :
Document clustering has been used as a core technique in managing vast amount of data and providing needed information. In on-line environments, generally new information gains more interests than old one. Traditional clustering focuses on grouping similar documents into clusters by treating each document with equal weight. We proposed a novelty-based incremental clustering method for on-line documents that has biases on recent documents. In the clustering method, the notion of ‘novelty’ is incorporated into a similarity function and a clustering method, a variant of the K-means method, is proposed. We examine the efficiency and behaviors of the method by experiments.
Keywords :
Clustering algorithms; Clustering methods; Data engineering; Data mining; Electronic mail; Engineering management; Radio broadcasting; Systems engineering and theory; TV broadcasting; Web and internet services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering Workshops, 2006. Proceedings. 22nd International Conference on
Conference_Location :
Atlanta, GA, USA
Print_ISBN :
0-7695-2571-7
Type :
conf
DOI :
10.1109/ICDEW.2006.100
Filename :
1623835
Link To Document :
بازگشت