A Cogitate Study on Text Mining
Y. Jahnavi1, Y. Radhika2
1Y. Jahnavi, Computer Science & Engineering Department, Research Scholar, GITAM University, India.
2Dr. Y. Radhika, Computer Science & Engineering Department Associate Professor, GITAM University, India.
Manuscript received on July 17, 2012. | Revised Manuscript received on August 25, 2012. | Manuscript published on August 30, 2012. | PP: 189-196 | Volume-1 Issue-6, August 2012.  | Retrieval Number: F0662081612/2012©BEIESP

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Abstract: The vast amount of digitalized textual content has given rise to the need for sophisticated text mining techniques. Text Mining is the process of analyzing and extracting the useful information from a set of semi structured and unstructured documents by applying machine learning and natural language processing techniques. It is easy for the people to assimilate from the categorized text documents. Even though a large research has evolved into this problem, there is a survey that indicated trends and directions. In this paper a cogitate study on preprocessing, term weighting algorithms, concept based term weighting algorithms, pattern discovery, categorization, domain ontology based frame work for text mining and summarization techniques is presented. In addition, a number of successful applications of text mining are discussed. 
Keywords: Classifiers, Term Weighting, Text Mining.