Smart Computing- Book ISBN- 978-81-953658-1-4

Authors:- Vraj Patel, Meet Soni, Janvi Patel

Abstract :-Rapid progress in digital data acquisition techniques have led to huge volume of data. More than 80 percent of today’s data is composed of unstructured or semi-structured data. The recovery of similar patterns and trends to see the text data from huge volume of data is a big issue. Text mining is a process of extracting interesting and nontrivial patterns from huge amount of text documents. There lie many techniques and tools to mine the text documents and discover the information for future and process in decision making. The choice of selecting the right and appropriate text mining technique helps to recover the speed and slows the time and effort required to get valuable information. This paper briefly discusses and analyzes the text mining techniques and their applications. With the advancement of technology, more and more data is available in digital form. Among which, most of the data (approx. 85%) is in unstructured textual form. Thus, it has become essential to build better techniques and algorithms to get useful and interesting data from the large amount of textual data. Hence, the field of information extraction and text mining became popular areas of research, to get interesting and needful information

Keywords: - Text Classification, Book Classification, K-Nearest Neighbor, Support Vector Machine, Naïve-Bayes, Convolutional Neural Network