A Review on Various Text Mining Techniques and Algorithms

Text mining is the method of extracting meaningful information or knowledge or patterns from the available text documents from various sources. The pattern discovery from the text and document organization of document is a well-known problem in data mining. At present world, the amount of stored information has been enormously increasing day by day which is generally in the unstructured form and cannot be used for any processing to extract useful information, so different techniques such as classification, clustering and information extraction are available under the category of text mining. In order to find an efficient and effective technique for text categorization, various techniques of text categorization is recently developed. Some of them are supervised and some of them unsupervised manner of document arrangement. In this paper, focus is text mining process, different method of text categorization, cluster analysis for text documents, the basic differences between relative terminologies on the basis of process, model and the algorithms used, a comparison between text mining techniques on the basis of algorithms, models and tools used. In addition of that a new text mining technique is proposed for future implementation