Towards A Knowledge Aware Ai
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Towards a Knowledge-Aware AI
Semantic systems lie at the heart of modern computing, interlinking with areas as diverse as AI, data science, knowledge discovery and management, big data analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence, enterprise vocabulary management, machine learning, logic programming, content engineering, social computing, and the Semantic Web. This book presents the proceedings of SEMANTiCS 2022, the 18th International Conference on Semantic Systems, held as a hybrid event – live in Vienna, Austria and online – from 12 to 15 September 2022. The SEMANTiCS conference is an annual meeting place for the professionals and researchers who make semantic computing work, who understand its benefits and encounter its limitations, and is attended by information managers, IT architects, software engineers, and researchers from organizations ranging from research facilities and NPOs, through public administrations to the largest companies in the world. The theme and subtitle of the 2022 conference was Towards A Knowledge-Aware AI, and the book contains 15 papers, selected on the basis of quality, impact and scientific merit following a rigorous review process which resulted in an acceptance rate of 29%. The book is divided into four chapters: semantics in data quality, standards and protection; representation learning and reasoning for downstream AI tasks; ontology development; and learning over complementary knowledge. Providing an overview of emerging trends and topics in the wide area of semantic computing, the book will be of interest to anyone involved in the development and deployment of computer technology and AI systems.
Towards a Knowledge-Aware AI
Semantic systems lie at the heart of modern computing, interlinking with areas as diverse as AI, data science, knowledge discovery and management, big data analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence, enterprise vocabulary management, machine learning, logic programming, content engineering, social computing, and the Semantic Web. This book presents the proceedings of SEMANTiCS 2022, the 18th International Conference on Semantic Systems, held as a hybrid event - live in Vienna, Austria and online - from 12 to 15 September 2022. The SEMANTiCS conference is an annual meeting place for the professionals and researchers who make semantic computing work, who understand its benefits and encounter its limitations, and is attended by information managers, IT architects, software engineers, and researchers from organizations ranging from research facilities and NPOs, through public administrations to the largest companies in the world. The theme and subtitle of the 2022 conference was Towards A Knowledge-Aware AI, and the book contains 15 papers, selected on the basis of quality, impact and scientific merit following a rigorous review process which resulted in an acceptance rate of 29%. The book is divided into four chapters: semantics in data quality, standards and protection; representation learning and reasoning for downstream AI tasks; ontology development; and learning over complementary knowledge. Providing an overview of emerging trends and topics in the wide area of semantic computing, the book will be of interest to anyone involved in the development and deployment of computer technology and AI systems.
Knowledge Graphs for Explainable Artificial Intelligence: Foundations, Applications and Challenges
The latest advances in Artificial Intelligence and (deep) Machine Learning in particular revealed a major drawback of modern intelligent systems, namely the inability to explain their decisions in a way that humans can easily understand. While eXplainable AI rapidly became an active area of research in response to this need for improved understandability and trustworthiness, the field of Knowledge Representation and Reasoning (KRR) has on the other hand a long-standing tradition in managing information in a symbolic, human-understandable form. This book provides the first comprehensive collection of research contributions on the role of knowledge graphs for eXplainable AI (KG4XAI), and the papers included here present academic and industrial research focused on the theory, methods and implementations of AI systems that use structured knowledge to generate reliable explanations. Introductory material on knowledge graphs is included for those readers with only a minimal background in the field, as well as specific chapters devoted to advanced methods, applications and case-studies that use knowledge graphs as a part of knowledge-based, explainable systems (KBX-systems). The final chapters explore current challenges and future research directions in the area of knowledge graphs for eXplainable AI. The book not only provides a scholarly, state-of-the-art overview of research in this subject area, but also fosters the hybrid combination of symbolic and subsymbolic AI methods, and will be of interest to all those working in the field.