Text Document Clustering Based on the Modifying Relations
Weixin Tian, Fuxi Zhu · 2008
Text document clustering plays an important role in the modern knowledge management. This paper addresses the task of developing an effective and efficient method of clustering the text document. To meet this requirement, we first extract the modifying relations (MR) from the sentences and then organize them as feature set for representing the document. A novel similarity measure is proposed on the basis of MR-vectors in this paper. We use agglomerative hierarchical clustering algorithm in the experimental work and compare the results with other previous studies.