Natural Language Processing: Transforming Human–Computer Interactions In Information Systems - JayaSudha, A R; Vigneshkumar, K; Manjula, M; Srinivasan, Praveen; Jayashree, V; Revathi, N; Pradeepkumar, S (Journal of Neonatal Surgery, 2025)
A key component of contemporary information systems, natural language processing (NLP) allows for more intuitive and natural interactions between people and machines. This chapter explores how NLP enhances information system interactions, offering a comprehensive overview of its core concepts, tools, and applications. Starting with an introduction to NLP, the chapter delves into its foundational techniques and key concepts, setting the stage for a deeper understanding of its evolution over time. The article highlights essential NLP tools and libraries, focusing on Python-based ecosystems for data preparation, visualization, and processing. It then examines the underlying technologies and algorithms that drive NLP systems, such as tokenization, parsing, and machine learning approaches. The transformative potential of NLP is illustrated through its diverse applications in information systems, including information retrieval, conversational agents, text summarization, and recommender systems. Real-world case studies are presented to showcase how these technologies are applied in practice. The discussion extends to the challenges that persist in NLP development, such as linguistic ambiguity, resource limitations, and ethical concerns. Finally, the chapter envisions the future of NLP in AI-driven systems, emphasizing emerging trends and its role in shaping next-generation intelligent systems. By bridging theoretical foundations with practical insights, this chapter aims to equip readers with a holistic understanding of NLP's potential and limitations in enhancing information system interactions