Auto Text Summarization with Categorization and Sentiment Analysis

Abstract

In today's world the volume of information is dramatically increasing, and the value of that information is growing fast. Modern organizations deals with terabytes of text, such as email, that often plays a significant role in their day-today operations. Even small and medium-sized organizations are dealing with growing volumes of text that require rapid access and meaningful analysis. Identifying useful information from these data is quite difficult and requires some mechanism. One possible means is to use text categorization and summarization. Text categorization is automatically arranging a set of documents into predefined categories and Summarization is a giving a condensed and precise depiction of input data such that the output includes the most significant concepts of the source. Sentiment analysis i.e. opinion mining states the use of NLP, text analysis and to identify and extract biased information in source materials.