A new cluster merging algorithm of Suffix Tree Clustering

Document clustering methods can be used to structure large sets of text or hypertext documents. Suffix Tree Clustering has been proved to be a good approach for documents clustering. However. the cluster merging algorithm of Suffix Tree Clustering is based on the over lap of their document sets, which totally ignore the similarity between the non-overlap parts of different Clusters. In this paper, we introduce a novel cluster merging approach which will combines the cosine similarity and overlap percentage. Using this method, we can get a better clustering result and a comparative small number of clusters.