Paper Title
Survey On Algorithms Used For Text Document Clustering

Document clustering is the process of segmenting a particular collection of texts into subgroups including content so that similar documents are in one group. It is also called text mining. The purpose of document clustering is served mainly in search engines and information retrieval from the database. Nowadays all paper documents are in electronic form, because of quick access and smaller storage. So, it is a major issue to retrieve relevant documents from the larger database. The goal is to transform text composed of everyday language in a structured, database format. In this way, heterogeneous documents are summarized and presented in a uniform manner. The challenging problems of document clustering are big volume, high dimensionality and complex semantics. Keywords— Text mining, Document clustering, K-means, Fuzzy C-means, Semantic Analysis