Text Analytics

Author:

Sameera Divanu1,Sharma Niraj2,Chary R.V. Ramana3

Affiliation:

1. CSE Department of SSSUTMS-Sehore, MP, India

2. Department of CSE, SSSUTMS-Sehore, India

3. Department of IT, B V Raju Institute of Technology, Narsapur, Medak, Telangana, India

Abstract

This chapter covers text analytics definitions, how to get started with text analytics, examples and approaches, and a case study. The chapter gives examples of existing text analytics applications to show the wide range of real-world implications. Finally, as a guide to text analytics and the book, we give a process road map. Chapter 2 (How to Get Started with Text Analytics) briefly explains the Analyse Your Data, Use BI Tools to Understand Your Data and Final Words. Chapter 3 (Examples and Methods for Text Analytics) explains various Text Analytics Approaches 1: Word Spotting Text Analytics Approach 2. Manual Rules Text Analytics Approach 3. Text Categorization Approach 4: Topic Modelling Approach and 5. Thematic Analysis. Applications of Word Spotting Text Analytics Approach, Manual Rules, Text Categorization Approach, Topic Modelling Approach and Thematic Analysis are discussed with real-time examples. Chapter 4 discusses the case study, the following real-time application, Word Cloud Explorer, to illustrate its analytic capabilities.

Publisher

BENTHAM SCIENCE PUBLISHERS

Reference77 articles.

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3. Burch M.; Lohmann S.; Beck F.; Rodriguez N.; Di Silvestro L.; Weiskopf D.; Radcloud: Visualizing multiple texts with merged word clouds. Information Visualisation (IV) 2014 18th International Conference on, 2014, pp. 108-113.

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