Natural Language Processing in Artificial Intelligence

✍ Scribed by Brojo Kishore Mishra, Raghvendra Kumar

• Publisher: Apple Academic Press
• Year: 2020
• Tongue: English
• Leaves: 297
• Edition: 1
• Category: Library

✦ Synopsis

This volume focuses on natural language processing, artificial intelligence, and allied areas.

Natural language processing enables communication between people and computers and

automatic translation to facilitate easy interaction with others around the world. This book

discusses theoretical work and advanced applications, approaches, and techniques for

computational models of information and how it is presented by language (artificial, human, or

natural) in other ways. It looks at intelligent natural language processing and related models of

thought, mental states, reasoning, and other cognitive processes. It explores the difficult

problems and challenges related to partiality, underspecification, and context-dependency, which

are signature features of information in nature and natural languages.

Key features:

• Addresses the functional frameworks and workflow that are trending in NLP and AI

• Looks at the latest technologies and the major challenges, issues, and advances

in NLP and AI

• Explores an intelligent field monitoring and automated system through AI with NLP

and its implications for the real world

• Discusses data acquisition and presents a real-time case study with illustrations related to

data-intensive technologies in AI and NLP

✦ Table of Contents

Cover
Half Title
Title Page
Copyright Page
About the Editors
Contents
Contributors
Abbreviations
Preface
1. A Survey on Social Business Intelligence: A Case Study of Application of Dynamic Social Networks for Decision Making
2. Critical Concepts and Techniques for Information Retrieval System
3. Futurity of Translation Algorithms for Neural Machine Translation (NMT) and Its Vision
4. Role of Machine Learning and Application Towards Information Retrieval in Cloud
5. Ontology-Based Information Retrieval and Matching in IoT Applications
6. Parts-of-Speech Tagging in NLP: Utility, Types, and Some Popular POS Taggers
7. Text Mining
8. A Brief Overview of Natural Language Processing and Artificial Intelligence
9. Use of Machine Learning and a Natural Language Processing Approach for Detecting Phishing Attacks
10. Role of Computational Intelligence in Natural Language Processing
Index