A comparative study of feature weighting methods for document co-clustering
Yunming Ye, Xutao Li, Biao Wu, Yan Li · International Journal of Information Technology Communications and Convergence · 2011
Document clustering is an important task in data mining. Co-clustering has become one of state-of-the-art methods for this task. In this paper, we propose a feature weighting co-clustering algorithm for document co-clustering and present a comparative study on how different weighting methods affect its performance. The compared feature weighting approaches include inverse document frequency-based methods, information theory-based methods and term variance-based methods. The comparison results on benchmark data sets show that the mutual information weighting method can lead to better performance for the proposed algorithm than other weighting schemes.