Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges

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Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges

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Author : I. Tiddi
language : en
Publisher: IOS Press
Release Date : 2020-05-06

Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges written by I. Tiddi and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-06 with Computers categories.

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.

Knowledge Graphs Semantics Machine Learning And Languages

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Author : M. Acosta
language : en
Publisher: IOS Press
Release Date : 2023-10-03

Knowledge Graphs Semantics Machine Learning And Languages written by M. Acosta and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-03 with Computers categories.

Semantic computing is an integral part of modern technology, an essential component of fields as diverse as artificial intelligence, data science, knowledge discovery and management, big data analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence, and enterprise vocabulary management. This book presents the proceedings of SEMANTICS 2023, the 19th International Conference on Semantic Systems, held in Leipzig, Germany, from 20 to 22 September 2023. The conference is a pivotal event for those professionals and researchers actively engaged in harnessing the power of semantic computing, an opportunity to increase their understanding of the subject’s transformative potential while confronting its practical limitations. Attendees include information managers, IT architects, software engineers, and researchers from a broad spectrum of organizations, including research facilities, non-profit entities, public administrations, and the world's largest corporations. For this year’s conference a total of 54 submissions were received in response to a call for papers. These were subjected to a rigorous, double-blind review process, with at least three independent reviews conducted for each submission. The 16 papers included here were ultimately accepted for presentation, with an acceptance rate of 29.6%. Areas covered include novel research challenges in areas such as data science, machine learning, logic programming, content engineering, social computing, and the Semantic Web. The book provides an up-to-date overview, which will be of interest to all those wishing to stay abreast of emerging trends and themes within the vast field of semantic computing.

Compendium Of Neurosymbolic Artificial Intelligence

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Author : P. Hitzler
language : en
Publisher: IOS Press
Release Date : 2023-08-04

Compendium Of Neurosymbolic Artificial Intelligence written by P. Hitzler and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-04 with Computers categories.

If only it were possible to develop automated and trainable neural systems that could justify their behavior in a way that could be interpreted by humans like a symbolic system. The field of Neurosymbolic AI aims to combine two disparate approaches to AI; symbolic reasoning and neural or connectionist approaches such as Deep Learning. The quest to unite these two types of AI has led to the development of many innovative techniques which extend the boundaries of both disciplines. This book, Compendium of Neurosymbolic Artificial Intelligence, presents 30 invited papers which explore various approaches to defining and developing a successful system to combine these two methods. Each strategy has clear advantages and disadvantages, with the aim of most being to find some useful middle ground between the rigid transparency of symbolic systems and the more flexible yet highly opaque neural applications. The papers are organized by theme, with the first four being overviews or surveys of the field. These are followed by papers covering neurosymbolic reasoning; neurosymbolic architectures; various aspects of Deep Learning; and finally two chapters on natural language processing. All papers were reviewed internally before publication. The book is intended to follow and extend the work of the previous book, Neuro-symbolic artificial intelligence: The state of the art (IOS Press; 2021) which laid out the breadth of the field at that time. Neurosymbolic AI is a young field which is still being actively defined and explored, and this book will be of interest to those working in AI research and development.

The Semantic Web Iswc 2020

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Author : Jeff Z. Pan
language : en
Publisher: Springer Nature
Release Date : 2020-10-31

The Semantic Web Iswc 2020 written by Jeff Z. Pan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-31 with Computers categories.

The two volume set LNCS 12506 and 12507 constitutes the proceedings of the 19th International Semantic Web Conference, ISWC 2020, which was planned to take place in Athens, Greece, during November 2-6, 2020. The conference changed to a virtual format due to the COVID-19 pandemic. The papers included in this volume deal with the latest advances in fundamental research, innovative technology, and applications of the Semantic Web, linked data, knowledge graphs, and knowledge processing on the Web. They were carefully reviewed and selected for inclusion in the proceedings as follows: Part I: Features 38 papers from the research track which were accepted from 170 submissions; Part II: Includes 22 papers from the resources track which were accepted from 71 submissions; and 21 papers in the in-use track, which had a total of 46 submissions. Chapter “Transparent Integration and Sharing of Life Cycle Sustainability Data with Provenance ” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Towards Ethical And Socially Responsible Explainable Ai

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Author : Mohammad Amir Khusru Akhtar
language : en
Publisher: Springer Nature
Release Date : 2024-08-30

Towards Ethical And Socially Responsible Explainable Ai written by Mohammad Amir Khusru Akhtar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-30 with Technology & Engineering categories.

"Dive deep into the evolving landscape of AI with 'Towards Ethical and Socially Responsible Explainable AI'. This transformative book explores the profound impact of AI on society, emphasizing transparency, accountability, and fairness in decision-making processes. It offers invaluable insights into creating AI systems that not only perform effectively but also uphold ethical standards and foster trust. Essential reading for technologists, policymakers, and all stakeholders invested in shaping a responsible AI future."

Further With Knowledge Graphs

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Author : M. Alam
language : en
Publisher: IOS Press
Release Date : 2021-09-23

Further With Knowledge Graphs written by M. Alam and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-23 with Computers categories.

The field of semantic computing is highly diverse, linking areas such as artificial intelligence, data science, knowledge discovery and management, big data analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence, and enterprise vocabulary management. As such it forms an essential part of the computing technology that underpins all our lives today. This volume presents the proceedings of SEMANTiCS 2021, the 17th International Conference on Semantic Systems. As a result of the continuing Coronavirus restrictions, SEMANTiCS 2021 was held in a hybrid form in Amsterdam, the Netherlands, from 6 to 9 September 2021. The annual SEMANTiCS conference provides an important platform for semantic computing professionals and researchers, and attracts information managers, IT­architects, software engineers, and researchers from a wide range of organizations, such as research facilities, NPOs, public administrations and the largest companies in the world. The subtitle of the 2021 conference’s was “In the Era of Knowledge Graphs”, and 66 submissions were received, from which the 19 papers included here were selected following a rigorous single-blind reviewing process; an acceptance rate of 29%. Topics covered include data science, machine learning, logic programming, content engineering, social computing, and the Semantic Web, as well as the additional sub-topics of digital humanities and cultural heritage, legal tech, and distributed and decentralized knowledge graphs. Providing an overview of current research and development, the book will be of interest to all those working in the field of semantic systems.

Decentralized Query Processing Over Heterogeneous Sources Of Knowledge Graphs

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Author : L. Heling
language : en
Publisher: IOS Press
Release Date : 2022-03-08

Decentralized Query Processing Over Heterogeneous Sources Of Knowledge Graphs written by L. Heling and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-08 with Computers categories.

Knowledge graphs are increasingly used in scientific and industrial applications. The large number and size of knowledge graphs published as Linked Data in autonomous sources has led to the development of various interfaces to query these knowledge graphs. Therefore, effective query processing approaches that enable efficient information retrieval from these knowledge graphs need to address the capabilities and limitations of different Linked Data Fragment interfaces. This book investigates novel approaches to addressing the challenges that arise in the presence of decentralized, heterogeneous sources of knowledge graphs. The effectiveness of these approaches is empirically evaluated and demonstrated using various real world and synthetic large-scale knowledge graphs throughout. First, a sample-based approach for generating fine-grained performance profiles is proposed, and it is demonstrated how the information from such profiles can be leveraged in cost model-based query planning. In addition, a sample-based data distribution profiling approach is advocated which aims to estimate the statistical profile features of large knowledge graphs and the applicability of these estimations in federated querying processing is demonstrated. The remainder of the book focuses on techniques to devise efficient query processing approaches when heterogeneous interfaces need to be queried but no fine-grained statistics are available. Robust techniques to support efficient query processing in these circumstances are investigated and results are shared to demonstrate the way in which these techniques can outperform state-of-the-art approaches. Finally, the author describes a framework for federated query processing over heterogeneous federations of Linked Data Fragments to exploit the capabilities of different sources by defining interface-aware approaches.

Artificial Intelligence In Medicine

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Author : Martin Michalowski
language : en
Publisher: Springer Nature
Release Date : 2022-07-08

Artificial Intelligence In Medicine written by Martin Michalowski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-08 with Computers categories.

This book constitutes the refereed proceedings of the 20th International Conference on Artificial Intelligence in Medicine, AIME 2022, held in Halifax, NS, Canada, in June 2022. The 39 full papers presented together with 7 short papers were selected from 113 submissions. The papers are grouped in topical sections on knowledge-based system; machine learning; medical image processing; predictive modeling; natural language processing.

Prediction And Analysis For Knowledge Representation And Machine Learning

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Author : Avadhesh Kumar
language : en
Publisher: CRC Press
Release Date : 2022-01-31

Prediction And Analysis For Knowledge Representation And Machine Learning written by Avadhesh Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-31 with Computers categories.

A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system’s perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems. Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the book’s website. Features: Examines the representational adequacy of needed knowledge representation Manipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original information Improves inferential and acquisition efficiency by applying automatic methods to acquire new knowledge Covers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technology Describes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarter This book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which includes both basic and advanced concepts.

Applied Data Science In Tourism

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Author : Roman Egger
language : en
Publisher: Springer Nature
Release Date : 2022-01-31

Applied Data Science In Tourism written by Roman Egger and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-31 with Business & Economics categories.

Access to large data sets has led to a paradigm shift in the tourism research landscape. Big data is enabling a new form of knowledge gain, while at the same time shaking the epistemological foundations and requiring new methods and analysis approaches. It allows for interdisciplinary cooperation between computer sciences and social and economic sciences, and complements the traditional research approaches. This book provides a broad basis for the practical application of data science approaches such as machine learning, text mining, social network analysis, and many more, which are essential for interdisciplinary tourism research. Each method is presented in principle, viewed analytically, and its advantages and disadvantages are weighed up and typical fields of application are presented. The correct methodical application is presented with a "how-to" approach, together with code examples, allowing a wider reader base including researchers, practitioners, and students entering the field. The book is a very well-structured introduction to data science – not only in tourism – and its methodological foundations, accompanied by well-chosen practical cases. It underlines an important insight: data are only representations of reality, you need methodological skills and domain background to derive knowledge from them - Hannes Werthner, Vienna University of Technology Roman Egger has accomplished a difficult but necessary task: make clear how data science can practically support and foster travel and tourism research and applications. The book offers a well-taught collection of chapters giving a comprehensive and deep account of AI and data science for tourism - Francesco Ricci, Free University of Bozen-Bolzano This well-structured and easy-to-read book provides a comprehensive overview of data science in tourism. It contributes largely to the methodological repository beyond traditional methods. - Rob Law, University of Macau