Paper Title
A Review Of Text Mining And Knowledge Discovery In Unstructured Text Analysis

Abstract
Abstract: Text mining (TM) is the process of discovering hidden meaning or information that is not known previously from unstructured text. Research interest in TM has been increasing due to the availability of huge amount of data on the internet. Researchers proposed several text mining techniques that help to discover new information from unstructured text. Some of the proposed text mining techniques include: NLP techniques, Naïve Bayes, and SVM. The TM techniques help in Sentiment Analysis, Text Summarization, Opinion Leaders, and Trends. There is need of gathering and analyzing the existing TM techniques so that researchers will find it easy to learn about the previous, current and future works. In this paper, we analyzed the existing text mining techniques, its challenges, limitations, future works and implemented a text classification with Naïve Bayes. Keywords: Text Mining Techniques, SVM, Naïve Bayes, Sentiment Analysis, Opinion Leaders, Text Summarization.

Author - Kaloma Usman Majikumna, Mustafa Ulas, Umit Ferit Aldim

Published : Volume-2, Issue-8  ( Aug, 2015 )

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