Enhancing Document Clustering Using Reweighting Terms Based on Semantic Features

摘要

This paper proposes a new document clustering method using the reweighted term based on semantic features for enhancing document clustering. The proposed method uses document samples of cluster by user to reduce the semantic gap between the user's requirement and clustering results by machine. The method can enhance the document clustering because it uses the reweighted term which can well represent an inherent structure of document set relevant to a user's requirement. The experimental results demonstrate that the proposed method achieves better performance than related document clustering methods.