Natural Language Processing in Artificial Intelligence

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 "This volume, Natural Language Processing in Artificial Intelligence, focuses on natural language processing (NLP), artificial intelligence (AI), and allied areas. The book delves into natural language processing, which enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world. It discusses theoretical work and advanced applications, approaches, and techniques for computational models of information and how it 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, under specification, 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, explores basic and high level concepts, thus serving as a resource for those in the industry while also helping beginners to understand both basic and advanced aspects, 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. Topics include the process of business intelligence and how this platform is used, the concepts of Information retrieval systems, the neural machine translation (NMT) process, the choice of words and text in natural language processing, embedded traffic control and management systems, a technique for generating ontology by adopting the fruit fly optimization algorithm, POS labeling using the Viterbi algorithm, how natural language processing techniques can be used to prevent phishing attacks, and more. This volume will be a useful and informative resource for faculty, advanced-level students, and professionals in the field of artificial intelligence, natural language processing, and other areas."-- Provided by publisher 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