This book presents a semantic-based explainable framework based on knowledge graph and semantic web technology. It focuses on designing XAI system that transforms black-box AI model into a comprehensive and meaningful AI model that users can leverage. Stack of technologies categorized under semantic web technologies is covered for the semantic explanation framework. It discussed ontology using OWL for capturing concepts and the relationship amongst concepts in the domain of discourse. Knowledge graph using Linked Open data (LOD) technology is covered for integrating formalized knowledge. The book also includes First Order Logic (FOL)-mathematical tool, as the foundation of knowledge representation and reasoning.
• Explain ability challenges of the existing deep learning-based AI model also termed as black box model, will be possible to be addressed by the implementation of the innovative technology.
• Enables to design of higher-level intelligence compared to the current AI system supports and thus revolutionises the entire automation domain.
• Assists AI professionals to get an insight into mathematical tools such as First Order Logic (FOL) and Description Logic(DL) for explicit knowledge representation.
• Helps to formalise knowledge required for machine intelligence using semantic web technologies
• Studies implications of XAI intelligent system developed for medical diagnosis, Fraud detection, Autonomous vehicles, hiring decisions, Legal decisions etc. for making decisions.
Researchers, students and professionals working on Computational Intelligence, Machine Learning, and Artificial Intelligence in the fields of computer science, computer engineering and information technology will find this book useful.
Table of Contents:
1. Integration of Deep Learning – based AI Model with Explainable AI (XAI) 2. Unlocking the Potential of Knowledge Graphs through Completion Techniques 3. Symbolic System, Neural Network and Semantic Web Technology Integration for Deep Learning 4. Mathematical Tools for Knowledge Representation 5. Cognitive Computational Systems Integrating Machine Learning and Automated Reasoning 6. Symbolic Knowledge Representation by ANN 7. Knowledge Representation for Human and Machine-Centric Explanations 8. Explainable AI: Bridging the Gap between Complexity and Interpretability 9. Interpretability, Transparency Assessment of AI Systems 10. Addressing Trustworthiness and Explainability Using Knowledge Graph 11. The Power of Automation: Exploring Robotic Process the Journey from Automation Theory to Implementation 12. Explainable Artificial Intelligence with Open Source Software 13. Knowledge Graph and Semantic Web Technology-based XAI Application of XAI in Different Domains 14. Developing Brain-Driven Systems Using Medical Image-Based Cognitive Intelligence and Machine Learning-Reasoning
About the Author :
T. Poongodi is currently working as a Professor in the School of Computing Science & Engineering at the Galgotias University, Delhi – NCR, India. She received her Ph.D. degree in Information Technology (Information and Communication Engineering) from Anna University, Tamil Nadu, India. Her current research interests include Network Security, Wireless Ad Hoc and Sensor Networks, Internet of Things (IoT), Computer Networks, and Blockchain Technology for emerging communication networks. She is CISCO, Oracle Academy certified, and handling networking, Structured Query Language courses. Dr. T. Poongodi is the author of over 40+ book chapters including some reputed publishers. She has published 15+ books in the areas of Internet of Things, Data Analytics, Blockchain Technology, Artificial Intelligence, Machine Learning, and Healthcare Informatics, published by reputed publishers.
Runumi Devi is presently working as an Associate Professor in the School of Computing Science & Engineering at the Galgotias University, Delhi – NCR, India. She received her Ph.D. degree in Information Technology (Semantic Framework for Sharing Data in an Interoperable Healthcare Environment) form Amity University, Noida, India. She did her MTech (Masters of Technology) in Computer Science & Engineering from GGSIP, Delhi, India and Master in Computer Applications from Jorhat Engineering College, Assam, India. Her current research interests include Ontology Engineering, Knowledge Engineering, Artificial Intelligence, Machine Learning, Semantic Web Technology. She is also RPA certified by UiPath Academy.
S. Prakash is working as an Assistant Professor in the School of Computing Science and Engineering, Presidency University, Bangalore, India. He is pursuing Ph.D. in Computer Science and Engineering, Galgotias University, Delhi - NCR, India. He has completed M.E in Computer Science and Engineering from Anna University, Tamil Nadu, India. His research interests include the Internet of Things, Natural Language Processing, Semantic Web, Cryptography and Network Security, Knowledge Engineering and Artificial Intelligence. He has published few articles in various International Journals, International Conferences, and book chapters in Scrivener Publishing. He received awards namely the Research and Innovation award on year of 2020 and 2021 from Galgotias University.
T. Ganesh Kumar received his Master of Engineering in Computer Science and Engineering from Manonmaniam Sundaranar University, Tirunelveli, India. He completed a Fulltime PhD in Computer Science and Engineering in the Department of Computer Science and Engineering at Manonmaniam Sundaranar University, Tirunelveli in the year 2016. Currently, He is working as an Associate Professor in the School of Computing Science & Engineering, Galgotias University, Greater Noida, Delhi NCR, India. He has published in many SCI and Scopus Indexed Journals. He has published many Indian patents and international patents.
