Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007) An Improved Semantic Smoothing Model for Model-Based Document Clustering Haier International Training Center, Qingdao, China July 30-August 01 ISBN: 0-7695-2909-7
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SNPD.2007.155
Recently, semantic smoothing is proposed as an efficient solution for the improvement of document cluster quality. However, the existing semantic smoothing model is not effective for partitional clustering to enhance the document clustering quality. In this paper, inspired by the TF*IDF schema and background elimination strategy, we first introduce an improved semantic smoothing model, which is suitable for both agglomerative and partitional clustering. Based on the improved semantic smoothing model, two model-document clustering algorithms, the partitional clustering algorithm and the agglomerative clustering algorithm, are also presented. The experimental results show our algorithms are more effective than the previous methods to improve the cluster quality.
Citation:
Jiarong Cai, Yubao Liu, Jian Yin, "An Improved Semantic Smoothing Model for Model-Based Document Clustering," snpd, vol. 3, pp.670-675, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007), 2007 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb