%0 Journal Article
%T Document Clustering Based on Semi-Supervised Term Clustering
%A Hamid Mahmoodi
%A Eghbal Mansoori
%J International Journal of Artificial Intelligence & Applications
%D 2012
%I Academy & Industry Research Collaboration Center (AIRCC)
%X The study is conducted to propose a multi-step feature (term) selection process and in semi-supervisedfashion, provide initial centers for term clusters. Then utilize the fuzzy c-means (FCM) clustering algorithm for clustering terms. Finally assign each of documents to closest associated term clusters. While most text clustering algorithms directly use documents for clustering, we propose to first group the terms using FCM algorithm and then cluster documents based on terms clusters. We evaluate effectiveness of our technique on several standard text collections and compare our results with the some classical text clustering algorithms.
%K Term Clustering
%K Fuzzy C-Means algorithm
%K Semi-supervised Feature Selection
%K Document Clustering
%U http://airccse.org/journal/ijaia/papers/3312ijaia06.pdf