An Improved Text Clustering Method based on Hybrid Model
According to the high-dimensional sparse features on the storage of textual document, and defects existing in the clustering methods or the hybrid methods which have already been studied by now and some other problems. So an improved text clustering method based on hybrid model, that is a text clustering approach (short for TGSOM-FS-FKM) based on Tree-structured Growing Self-Organizing Maps (TGSOM) and Fuzzy K-Means (FKM) is proposed. The method has optimized the clustering result through three times of clustering. It firstly makes preprocess of texts, and filters the majority of noisy words by using an unsupervised feature selection method.