Reasoning Web. Explainable Artificial Intelligence

Author: Markus Krötzsch

Publisher: Springer Nature

ISBN: 9783030314231

Category: Computers

Page: 283

View: 869

This volume contains lecture notes of the 15th Reasoning Web Summer School (RW 2019), held in Bolzano, Italy, in September 2019. The research areas of Semantic Web, Linked Data, and Knowledge Graphs have recently received a lot of attention in academia and industry. Since its inception in 2001, the Semantic Web has aimed at enriching the existing Web with meta-data and processing methods, so as to provide Web-based systems with intelligent capabilities such as context awareness and decision support. The Semantic Web vision has been driving many community efforts which have invested a lot of resources in developing vocabularies and ontologies for annotating their resources semantically. Besides ontologies, rules have long been a central part of the Semantic Web framework and are available as one of its fundamental representation tools, with logic serving as a unifying foundation. Linked Data is a related research area which studies how one can make RDF data available on the Web and interconnect it with other data with the aim of increasing its value for everybody. Knowledge Graphs have been shown useful not only for Web search (as demonstrated by Google, Bing, etc.) but also in many application domains.
Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges

Author: I. Tiddi

Publisher: IOS Press

ISBN: 9781643680811

Category: Computers

Page: 314

View: 909

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.
Rules and Reasoning

Author: Víctor Gutiérrez-Basulto

Publisher: Springer Nature

ISBN: 9783030579777

Category: Computers

Page: 187

View: 156

This book constitutes the proceedings of the International Joint Conference on Rules and Reasoning, RuleML+RR 2020, held in Oslo, Norway, during June-July 2020*. This is the 4th conference of a new series, joining the efforts of two existing conference series, namely “RuleML” (International Web Rule Symposium) and “RR” (Web Reasoning and Rule Systems). The 7 full research papers presented together with 6 short technical communications papers were carefully reviewed and selected from 30 submissions. *The conference was held virtually due to the COVID-19 pandemic.
Reasoning Web. Declarative Artificial Intelligence

Author: Marco Manna

Publisher: Springer Nature

ISBN: 9783030600679

Category: Computers

Page: 255

View: 583

This volume contains 8 lecture notes of the 16th Reasoning Web Summer School (RW 2020), held in Oslo, Norway, in June 2020. The Reasoning Web series of annual summer schools has become the prime educational event in the field of reasoning techniques on the Web, attracting both young and established researchers. The broad theme of this year's summer school was “Declarative Artificial Intelligence” and it covered various aspects of ontological reasoning and related issues that are of particular interest to Semantic Web and Linked Data applications. The following eight lectures have been presented during the school: Introduction to Probabilistic Ontologies, On the Complexity of Learning Description Logic Ontologies, Explanation via Machine Arguing, Stream Reasoning: From Theory to Practice, First-Order Rewritability of Temporal Ontology-Mediated Queries, An Introduction to Answer Set Programming and Some of Its Extensions, Declarative Data Analysis using Limit Datalog Programs, and Knowledge Graphs: Research Directions.
Machine Learning, Optimization, and Data Science

Author: Giuseppe Nicosia

Publisher: Springer Nature

ISBN: 9783030954673

Category: Application software

Page: 667

View: 117

This two-volume set, LNCS 13163-13164, constitutes the refereed proceedings of the 7th International Conference on Machine Learning, Optimization, and Data Science, LOD 2021, together with the first edition of the Symposium on Artificial Intelligence and Neuroscience, ACAIN 2021. The total of 86 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 215 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
Robotic Surgery

Author: Farid Gharagozloo

Publisher: Springer Nature

ISBN: 9783030535940

Category: Medical

Page: 1599

View: 256

The first edition of Robotic Surgery was written only a decade after the introduction of robotic technology. It was the first comprehensive robotic surgery reference and represented the early pioneering look ahead to the future of surgery. Building upon its success, this successor edition serves as a complete multi-specialty sourcebook for robotic surgery. It seeks to explore an in-depth look into surgical robotics and remote technologies leading to the goal of achieving the benefits of traditional surgery with the least disruption to the normal functions of the human body. Written by experts in the field, chapters cover the fundamental principles of robotic surgery and provide clear instruction on their clinical application and long term results. Most notably, one chapter on “The Blueprint for the Establishment of a Successful Robotic Surgery Program: Lessons from Admiral Hymen R. Rickover and the Nuclear Navy” outlines the many valuable lessons from the transformative change which was brought about by the introduction of nuclear technology into the conventional navy with Safety as the singular goal of the change process. Robotics represents a monumental triumph of surgical technology. Undoubtedly, the safety of the patient will be the ultimate determinant of its success. The second edition of Robotic Surgery aims to erase the artificial boundaries of specialization based on regional anatomy and serves as a comprehensive multispecialty reference for all robot surgeons. It allows them to contemplate crossing boundaries which are historically defined by traditional open surgery.
Explainable Artificial Intelligence for Cyber Security

Author: Mohiuddin Ahmed

Publisher: Springer Nature

ISBN: 9783030966300

Category: Artificial intelligence

Page: 283

View: 133

This book presents that explainable artificial intelligence (XAI) is going to replace the traditional artificial, machine learning, deep learning algorithms which work as a black box as of today. To understand the algorithms better and interpret the complex networks of these algorithms, XAI plays a vital role. In last few decades, we have embraced AI in our daily life to solve a plethora of problems, one of the notable problems is cyber security. In coming years, the traditional AI algorithms are not able to address the zero-day cyber attacks, and hence, to capitalize on the AI algorithms, it is absolutely important to focus more on XAI. Hence, this book serves as an excellent reference for those who are working in cyber security and artificial intelligence.
Towards Digital Intelligence Society

Author: Ján Paralič

Publisher: Springer Nature

ISBN: 9783030638726

Category: Technology & Engineering

Page: 204

View: 145

This book aims to provide readers with up-to-date knowledge on how to make these technologies smarter. Humanity is now going through difficult times to fight the Covid-19 pandemic. Simultaneously, in these difficult times of physical separation, we can also realize how much digital society technology helps us cope with many difficulties that bring us this time. The authors focus on selected research challenges for intelligent digital society and state-of-the-art methods of how to face them. The book’s subtitle suggests that a core concept that the reader can study from various points of view in particular book chapters is the knowledge. The knowledge that can help us intelligently face different digital society challenges (Part I of this book); the knowledge extracted from available big data employing intelligent analysis techniques (Part II). For efficient processing and analysis of data, there is a strong need for smart data and information modeling techniques (Part III).
Knowledge Graphs

Author: Aidan Hogan

Publisher: Morgan & Claypool Publishers

ISBN: 9781636392363

Category: Computers

Page: 257

View: 466

This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve. This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.
Formal Concept Analysis

Author: Agnès Braud

Publisher: Springer Nature

ISBN: 9783030778675

Category: Computers

Page: 299

View: 757

This book constitutes the proceedings of the 16th International Conference on Formal Concept Analysis, ICFCA 2021, held in Strasbourg, France, in June/July 2021. The 14 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 32 submissions. The book also contains four invited contributions in full paper length. The research part of this volume is divided in five different sections. First, "Theory" contains compiled works that discuss advances on theoretical aspects of FCA. Second, the section "Rules" consists of contributions devoted to implications and association rules. The third section "Methods and Applications" is composed of results that are concerned with new algorithms and their applications. "Exploration and Visualization" introduces different approaches to data exploration.
Explainable AI Within the Digital Transformation and Cyber Physical Systems

Author: Moamar Sayed-Mouchaweh

Publisher: Springer Nature

ISBN: 9783030764098

Category: Technology & Engineering

Page: 198

View: 994

This book presents Explainable Artificial Intelligence (XAI), which aims at producing explainable models that enable human users to understand and appropriately trust the obtained results. The authors discuss the challenges involved in making machine learning-based AI explainable. Firstly, that the explanations must be adapted to different stakeholders (end-users, policy makers, industries, utilities etc.) with different levels of technical knowledge (managers, engineers, technicians, etc.) in different application domains. Secondly, that it is important to develop an evaluation framework and standards in order to measure the effectiveness of the provided explanations at the human and the technical levels. This book gathers research contributions aiming at the development and/or the use of XAI techniques in order to address the aforementioned challenges in different applications such as healthcare, finance, cybersecurity, and document summarization. It allows highlighting the benefits and requirements of using explainable models in different application domains in order to provide guidance to readers to select the most adapted models to their specified problem and conditions. Includes recent developments of the use of Explainable Artificial Intelligence (XAI) in order to address the challenges of digital transition and cyber-physical systems; Provides a textual scientific description of the use of XAI in order to address the challenges of digital transition and cyber-physical systems; Presents examples and case studies in order to increase transparency and understanding of the methodological concepts.
Computer Safety, Reliability, and Security

Author: António Casimiro

Publisher: Springer Nature

ISBN: 9783030545499

Category: Computers

Page: 450

View: 875

This book constitutes the proceedings of the 39th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2020, held in Lisbon, Portugal, in September 2020.* The 27 full and 2 short papers included in this volume were carefully reviewed and selected from 116 submissions. They were organized in topical sections named: safety cases and argumentation; formal verification and analysis; security modelling and methods; assurance of learning-enabled systems; practical experience and tools; threat analysis and risk mitigation; cyber-physical systems security; and fault injection and fault tolerance. *The conference was held virtually due to the COVID-19 pandemic. The chapter ‘Assurance Argument Elements for Off-the-Shelf, Complex Computational Hardware’ is available open access under an Open Government License 3.0 via link.springer.com.