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A Document Clustering Technique Based on Term Clustering and Association Rules

机译:基于术语群集和关联规则的文档聚类技术

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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.
机译:随着互联网和数据库技术的发展,网络挖掘从信息科学域中有更多和更多的注意。本文提出了一种基于术语聚类和关联规则的文档聚类技术。在该技术中,首先从文档集合中提取单词,然后根据AMI(常用相互信息)构造术语群集,文档VSM(向量空间模型)由术语群集表示,并使用关联规则到挖掘文档群集。实验结果表明,这种技术的性能和聚类质量比聚类过程中的传统方法的性能和聚类质量得到改善。

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