A Review Of Text Mining And Knowledge Discovery In Unstructured Text Analysis
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.