Nandana Mihindukulasooriya – författare

Knowledge Graphs and Large Language Models: Current Approaches, Challenges, and Future Directions explores the cutting-edge fusion of two powerful artificial intelligence technologies: Large Language Models (LLMs) and Knowledge Graphs (KGs). The book is structured to provide a comprehensive understanding of this emerging field. Chapters introduce the synergy between LLMs and KGs, delve into the capabilities and challenges of LLMs, focus on the structure, function, and significance of KGs, present a conceptual framework for bridging LLMs and KGs, discuss techniques for their integration, explore how LLMs can enhance KGs and vice versa, and showcase applications of LLM-KG synergy across various domains.Final sections addresses ethical, social, and technical challenges and future innovations. The book concludes by summarizing key insights and advancements in intelligent systems. This is an essential resource for graduate students, researchers, and professionals in computer science. It offers valuable insights for adopting LLMs, KGs, and their advanced applications in research and product development. By bridging the gap between these technologies, this book equips readers with the knowledge to drive innovation and enhance the capabilities of intelligent systems.Explores integration techniques for combining LLMs and KGsEnhances understanding of AI applications with context and accuracyProvides practical insights through real-world case studiesAddresses ethical and technical challenges in LLM-KG synergy

The topics covered in this volume are data mining, patient electronic health records, healthcare portals, telemedicine, automatic identification and data collector systems, RFID and localization techniques, usability and ubiquity in e-Health, artificial intelligence for healthcare decision-making, etc.

The topics covered in this volume are data mining, patient electronic health records, healthcare portals, telemedicine, automatic identification and data collector systems, RFID and localization techniques, usability and ubiquity in e-Health, artificial intelligence for healthcare decision-making, etc.