A Review on Knowledge Discovery using Text Classification Techniques in Text Mining

Data mining is process of identify the knowledge from large data set. Knowledge discovery from textual database is a process of extracting interested or non retrival pattern from unstructured text document. With rapid growing of information increasing trends in people to extract knowledge from large text document. A text mining frame work contain preprocess on text and techniques used to retrieve information like classification, clustering, summarization, information extraction, and visualization.. There are several text classification techniques are review in this review paper such as SVM, Naïve bayes, KNN, Association rule, and decision tree classifier. Which categorized the text data in to pre define class. In this review paper we study deferent techniques of text mining to extracting relevant information on demand. The goal of the paper is to review and understand different text classification techniques and finding the best one out for different prospective. From reviews I propose method with the use best classification method to improve the performance of result and improve indexing. And show the comparison of different classification techniques