document: A new suffix tree similarity measure for document clustering In this paper , we propose a new similarity measure to compute the pairwise similarity of text-based documents based on suffix tree document model . By applying the new suffix tree similarity measure in Group-average Agglomerative Hierarchical Clustering ( GAHC ) algorithm , we developed a new suffix tree document clustering algorithm ( NSTC ) . Experimental results on two standard document clustering benchmark corpus OHSUMED and RCV1 indicate that the new clustering algorithm is a very effective document clustering algorithm . Comparing with the results of traditional word term weight tf-idf similarity measure in the same GAHC algorithm , NSTC achieved an improvement of 51 % on the average of F-measure score . Furthermore , we apply the new clustering algorithm in analyzing the Web documents in online forum communities . A topic oriented clustering algorithm is developed to help people in assessing , classifying and searching the the Web documents in a large forum community .
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