A Topical Document Clustering Method
Sheng Li · Zhongwen xinxi xuebao · 2007
Few of the existing document clustering methods can detect or describe document topics properly,which makes it difficult to conduct clustering based on topics.In this paper,we introduce a novel topical document clustering method called Linguistic Features Indexing Clustering(LFIC),which can identify topics accurately and cluster documents according to these topics.In LFIC,topic elements are defined and extracted for indexing base clusters.Additionally,linguistic features are exploited.Experimental results show that LFIC can gain a higher precision(94.66%) than some widely used traditional clustering methods.