期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2012
卷号：9
期号：1
出版社：IJCSI Press
摘要：With the rapid development of web content, retrieving relevant information is difficult task. The efficient clustering algorithms are needed to improve the results of the retrieval. Document clustering is a process of recognizing the similarity or dissimilarity among the given objects and forms subgroups sharing common characteristics. In this paper, we propose a semantic text document clustering approach that using WordNet lexical and Self Organizing Maps. The proposed approach uses the WordNet to identify the importance of the concepts in the document. The SOM is used to cluster the document. We use this approach to enhance the effectiveness of document clustering algorithms. The approach takes the advantages of the semantics available in knowledge base and the relationship between the words in the input documents. Some experiments are performed to compare efficiency of the proposed approach with the recently reported approaches. Experiments show advantage of the proposed approach over the others.
