A process of taking words as a input and predict the next word in the sequence.
Published in Chapter:
Machine Learning in Text Analysis
Neha Garg (Manav Rachna International Institute of Research and Studies, India) and Kamlesh Sharma (Manav Rachna International Institute of Research and Studies, India)
Copyright: © 2020
|Pages: 20
DOI: 10.4018/978-1-5225-9643-1.ch018
Abstract
This chapter provides a basic understanding of processes and models needed to investigate the data posted by users on social networking sites like Facebook, Twitter, Instagram, etc. Often the databases of social networking sites are large and can't be handled using traditional methodology for analysis. Moreover, the data is posted in such a random manner that can't be used directly for the analysis purpose; therefore, a considerable preprocessing is needed to use that data and generate important results that can help in decision making for various areas like sentiment analysis, customer feedback, customer reviews for brand and product, prevention management, risk management, etc. Therefore, this chapter is discussing various aspects of text and its structure, various machine learning algorithms and their types, why machine learning is better for text analysis, the process of text analysis with the help of examples, issues associated with text analysis, and major application areas of text analysis.