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Full Description
This book offers a comprehensive and application-oriented exploration of Artificial Intelligence and Natural Language Processing (NLP), addressing both foundational principles and modern, data-driven methodologies. It is designed to equip readers with a deep understanding of how intelligent systems learn from data, interpret human language, and support automated decision-making across real-world contexts.
Natural Language Processing for Business and Organizations: Research and Innovation cover key areas such as machine learning, deep learning, text representation, language modeling, information extraction, sentiment analysis, and AI-driven analytics, while also discussing system design considerations for deploying NLP solutions at scale. Through carefully structured chapters, the book integrates theoretical insights with practical examples, case studies, and applied workflows, enabling readers to translate algorithms and models into effective AI applications. Written by a team of academic researchers and industry practitioners, the book emphasizes responsible and value-driven AI, including ethical considerations, data quality, and model evaluation.
This book is written for advanced undergraduate and postgraduate students, researchers, and professionals seeking to build, evaluate, and apply AI and NLP systems in academic, enterprise, and societal domains.
Contents
1. NLP's Strategic Role in Business Transformation: Foundations, Impact, and Integration 2. Next-Gen Customer Intelligence: NLP for Voice of Customer (VoC) & CX Analytics 3. Deal Desk Acceleration: Contract Analytics, Redlining, and Compliance Automation 4. Financial Narrative Intelligence: Natural Language Processing Applications in Earnings Call Analysis, ESG Disclosure Mining and 10-K Filings 5. Real-time Competitive Intelligence: Market Sentiment, News Streams & M&A Surveillance 6. The Future of AI Chatbots in Education and Business: Towards More Intelligent and Inclusive Real-World Systems 7. Empowering Natural Language Processing through Big Data Analytics and Cloud Platforms 8. Leveraging LLM for Business Intelligence: Summarization, Chatbots, and Performance Evaluation 9. Operational NLP in Capital Markets: Engineering, MLOps, and Explainability on Earnings Calls, ESG, and Workflows - Systems, Governance and Evaluation 10. Intelligent Document Workflows: NLP for Invoice Processing, AP Automation & E-Discovery 11. Multimodal Enterprise Knowledge Graphs: Business Ontologies and Insights Mining 12. Generative AI in the Enterprise: Autonomous Agents for Business Process Automation
