Dynamic Fluzzy Clustering Algorithm for Web Documents Mining
Qi Luo · 2010
This paper first studies the methods of web documents mining and text clustering, and summaries the fuzzy clustering algorithms and similarity measure functions, then proposes a modified similarity function which can solve the problems of feature selection and feature extraction in high-dimensional space. Finally, this paper puts forward to a dynamic fluzzy clustering algorithm(DCFCM) by combining the proposed similarity function with approximated C-mediods. The experiments show that DCFCM can effectively improve he precision of web documents clustering, the method is feasible in web documents mining.