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http://dx.doi.org/10.6109/jkiice.2014.18.3.625

Document Clustering Technique by K-means Algorithm and PCA  

Kim, Woosaeng (Department of Computer Software, Kwangwoon University)
Kim, Sooyoung (Department of Computer Engineering, Handong Global University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.18, no.3, 2014 , pp. 625-630 More about this Journal
Abstract
The amount of information is increasing rapidly with the development of the internet and the computer. Since these enormous information is managed by the document forms, it is necessary to search and process them efficiently. The document clustering technique which clusters the related documents through the similarity between the documents help to classify, search, and process the large amount of documents automatically. This paper proposes a method to find the initial seed points through principal component analysis when the documents represented by vectors in the feature vector space are clustered by K-means algorithm in order to increase clustering performance. The experiment shows that our method has a better performance than the traditional K-means algorithm.
Keywords
Document Clustering; K-means algorithm; PCA;
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