Document Clustering Based on Semi-Supervised Term Clustering

Abstract

The study is conducted to propose a multi-step feature (term) selection process and in semi-supervised fashion, 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.