Text Analytics

- Authors: Divanu Sameera1, Niraj Sharma2, R.V. Ramana Chary3
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View Affiliations Hide Affiliations1 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
- Source: Handbook of Artificial Intelligence , pp 165-194
- Publication Date: November 2023
- Language: English
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.
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