Towards a Knowledge-Aware AI

Towards a Knowledge-Aware AI PDF Author: A. Dimou
Publisher: IOS Press
ISBN: 1643683217
Category : Computers
Languages : en
Pages : 236

Book Description
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

Towards a Knowledge-Aware AI PDF Author: A. Dimou
Publisher:
ISBN: 9781643683201
Category :
Languages : en
Pages : 0

Book Description
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 Representation

Knowledge Representation PDF Author: T.J.M. Bench-Capon
Publisher: Elsevier
ISBN: 1483297101
Category : Computers
Languages : en
Pages : 220

Book Description
Although many texts exist offering an introduction to artificial intelligence (AI), this book is unique in that it places an emphasis on knowledge representation (KR) concepts. It includes small-scale implementations in PROLOG to illustrate the major KR paradigms and their developments.****back cover copy:**Knowledge representation is at the heart of the artificial intelligence enterprise: anyone writing a program which seeks to work by encoding and manipulating knowledge needs to pay attention to the scheme whereby he will represent the knowledge, and to be aware of the consequences of the choices made.****The book's distinctive approach introduces the topic of AI through a study of knowledge representation issues. It assumes a basic knowledge of computing and a familiarity with the principles of elementary formal logic would be advantageous.****Knowledge Representation: An Approach to Artificial Intelligence develops from an introductory consideration of AI, knowledge representation and logic, through search technique to the three central knowledge paradigms: production rules, structured objects, and predicate calculus. The final section of the book illustrates the application of these knowledge representation paradigms through the Prolog Programming language and with an examination of diverse expert systems applications. The book concludes with a look at some advanced issues in knowledge representation.****This text provides an introduction to AI through a study of knowledge representation and each chapter contains exercises for students. Experienced computer scientists and students alike, seeking an introduction to AI and knowledge representations will find this an invaluable text.

Embedding Knowledge Graphs with RDF2vec

Embedding Knowledge Graphs with RDF2vec PDF Author: Heiko Paulheim
Publisher: Springer Nature
ISBN: 3031303873
Category : Computers
Languages : en
Pages : 165

Book Description
This book explains the ideas behind one of the most well-known methods for knowledge graph embedding of transformations to compute vector representations from a graph, known as RDF2vec. The authors describe its usage in practice, from reusing pre-trained knowledge graph embeddings to training tailored vectors for a knowledge graph at hand. They also demonstrate different extensions of RDF2vec and how they affect not only the downstream performance, but also the expressivity of the resulting vector representation, and analyze the resulting vector spaces and the semantic properties they encode.

Legal Knowledge and Information Systems

Legal Knowledge and Information Systems PDF Author: G. Sileno
Publisher: IOS Press
ISBN: 1643684736
Category : Computers
Languages : en
Pages : 422

Book Description
Technological advances related to legal information, knowledge representation, engineering, and processing have aroused growing interest within the research community and the legal industry in recent years. These advances relate to areas such as computational and formal models of legal reasoning, legal data analytics, legal information retrieval, the application of machine learning techniques to different legal tasks, and the experimental evaluation of these systems. This book presents the proceedings of JURIX 2023, the 36th International Conference on Legal Knowledge and Information Systems, held from 18–20 December 2023 in Maastricht, the Netherlands. This annual conference has become recognized as an international forum where academics and professionals working at the intersection of law and artificial intelligence can exchange knowledge and experience. A total of 92 submissions were received for the conference, of which 18 were selected as long papers, 30 as short papers and 7 as demo papers following a rigorous review process. This represents an acceptance rate of around 20% for long papers (60% overall). Topics covered include formal approaches applied to various aspects of legal reasoning; machine learning and information retrieval methods applied to various natural language processing tasks; hybrid approaches to working on the frontier between symbolic and sub-symbolic methods; experimental inquiries into the interfaces between computational systems and legal systems; and network analysis in law. Providing a comprehensive overview of recent advances in the field, the book will be of interest to all those working at the intersection between law and AI.

Systems, Software and Services Process Improvement

Systems, Software and Services Process Improvement PDF Author: Murat Yilmaz
Publisher: Springer Nature
ISBN: 3031423070
Category : Business & Economics
Languages : en
Pages : 403

Book Description
This two-volume set constitutes the refereed proceedings of the 30th European Conference on Systems, Software and Services Process Improvement, EuroSPI 2023, held in Grenoble, France, in August-September 2023. The 47 full papers presented were carefully reviewed and selected from 100 submissions. The papers are organized according to the following topical sections: SPI and emerging and multidisciplinary approaches to software engineering; digitalisation of industry, infrastructure and e-mobility; SPI and good/bad SPI practices in improvement; SPI and functional safety and cybersecurity; SPI and agile; SPI and standards and safety and security norms; sustainability and life cycle challenges; SPI and recent innovations; virtual reality and augmented reality.

Knowledge Graphs: Semantics, Machine Learning, and Languages

Knowledge Graphs: Semantics, Machine Learning, and Languages PDF Author: M. Acosta
Publisher: IOS Press
ISBN: 1643684256
Category : Computers
Languages : en
Pages : 262

Book Description
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.

Multilinguality in Knowledge Graphs

Multilinguality in Knowledge Graphs PDF Author: L.-A. Kaffee
Publisher: IOS Press
ISBN: 1643684558
Category : Computers
Languages : en
Pages : 218

Book Description
Content on the web is predominantly written in English, making it inaccessible to those who only speak other languages. Knowledge graphs can store multilingual information, facilitate the creation of multilingual applications, and make content accessible to multiple language communities. This book, Multilinguality in Knowledge Graphs, presents studies which assess and improve the state of labels and languages in knowledge graphs and the application of multilingual information. The author proposes ways of using multilingual knowledge graphs to reduce the gaps in coverage between languages, and the book explores the current state of language distribution in knowledge graphs by developing a framework based on existing standards, frameworks, and guidelines to measure label and language distribution in knowledge graphs. Applying this framework to a dataset representing the web of data, and to Wikidata, both a lack of labeling on the web and a bias towards a small set of languages were found. The book explores how a knowledge of labels and languages can be used in the domain of answering questions, and demonstrates how the framework can be applied to the task of ranking and selecting knowledge graphs for a set of user questions. Transliteration and translation of knowledge graph labels and aliases are also covered, as is the automatic classification of labels into one or the other to train a model for each task. The book provides a wide range of information on working with data and knowledge graphs in less-resourced languages.

Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges

Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, Applications and Challenges PDF Author: I. Tiddi
Publisher: IOS Press
ISBN: 1643680811
Category : Computers
Languages : en
Pages : 314

Book Description
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.

Empirical Ontology Design Patterns

Empirical Ontology Design Patterns PDF Author: V.A. Carriero
Publisher: IOS Press
ISBN: 1643684795
Category : Computers
Languages : en
Pages : 154

Book Description
In recent years, knowledge graphs (KGs) and ontologies have been widely adopted for modeling many kinds of domain. They are frequently released openly, something which benefits those who are starting new projects, because it offers them a wide choice of ontology reuse and the possibility to link to existing data. Understanding the content of an ontology or a knowledge graph is far from straightforward, however, and existing methods address this issue only partially, while exploring and comparing multiple ontologies can be a tedious manual task. This book, Empirical Ontology Design Patterns, starts from the premise that identifying the Ontology Design Patterns (ODPs) used in an ontology or a knowledge graph will go some way to addressing this problem. Its main focus is to provide tools which will effectively support the task of automatically identifying ODPs in existing ontologies and knowledge graphs. The book analyses the role of ODPs in ontology engineering, placing this analysis in the wider context of existing approaches to ontology reuse and implementation. It introduces a novel method for extracting empirical ontology design patterns (EODPs) from ontologies, and another for extracting EODPs from knowledge graphs whose schemas are implicit. Both methods are applied to ontologies and knowledge graphs frequently adopted and reused, such as Wikidata. The book also offers an ontology which can be used as a basis for annotating ODPs in ontologies and knowledge graphs, whether manually or automatically. The book will be of interest to all those whose work involves the use or reuse of ontologies and knowledge graphs.