Text Mining: Techniques, Applications and Issues

TLDR

Rapid progress in digital data acquisition has produced vast volumes of largely unstructured data, making pattern discovery in text documents a major challenge. This paper briefly discusses and analyzes text mining techniques and their applications across diverse fields. It also identifies issues that affect the accuracy and relevance of results in text mining.

Abstract

Rapid progress in digital data acquisition tech-niques have led to huge volume of data. More than 80 percent of today’s data is composed of unstructured or semi-structured data. The discovery of appropriate patterns and trends to analyze the text documents from massive volume of data is a big issue. Text mining is a process of extracting interesting and non-trivial patterns from huge amount of text documents. There exist different techniques and tools to mine the text and discover valuable information for future prediction and decision making process. The selection of right and appropriate text mining technique helps to enhance the speed and decreases the time and effort required to extract valuable information. This paper briefly discuss and analyze the text mining techniques and their applications in diverse fields of life. Moreover, the issues in the field of text mining that affect the accuracy and relevance of results are identified.