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Abstract

Knowledge and Inference discusses an important problem for software systems: How do we treat knowledge and ideas on a computer and how do we use inference to solve problems on a computer? The book talks about the problems of knowledge and inference for the purpose of merging artificial intelligence and library science. The book begins by clarifying the concept of ""knowledge"" from many points of view, followed by a chapter on the current state of library science and the place of artificial intelligence in library science. Subsequent chapters cover central topics in the artificial intelligence: search and problem solving, methods of making proofs, and the use of knowledge in looking for a proof. There is also a discussion of how to use the knowledge system. The final chapter describes a popular expert system. It describes tools for building expert systems using an example based on Expert Systems-A Practical Introduction by P. Sell (Macmillian, 1985). This type of software is called an ""expert system shell."" This book was written as a textbook for undergraduate students covering only the basics but explaining as much detail as possible.

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Abstract

The development of thinking machines is an adventure as bold and ambitious as any that humans have attempted. And the truth is that Artificial Intelligence is already an indispensable part of our daily lives. Without it, Google wouldn't have answers and your smartphone would just be a phone. But how will AI change society by 2050? Will it destroy jobs? Or even pose an existential threat? Android Dreams is a lively exploration of how AI will transform our societies, economies and selves. From robot criminals to cyber healthcare, and a sky full of empty planes, Toby Walsh's predictions about AI are guaranteed to surprise you.

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Abstract

Metadata research has emerged as a discipline cross-cutting many domains, focused on the provision of distributed descriptions (often called annotations) to Web resources or applications. Such associated descriptions are supposed to serve as a foundation for advanced services in many application areas, including search and location, personalization, federation of repositories and automated delivery of information. Indeed, the Semantic Web is in itself a concrete technological framework for ontology-based metadata. For example, Web-based social networking requires metadata describing people and their interrelations, and large databases with biological information use complex and detailed metadata schemas for more precise and informed search strategies. There is a wide diversity in the languages and idioms used for providing meta-descriptions, from simple structured text in metadata schemas to formal annotations using ontologies, and the technologies for storing, sharing and exploiting meta-descriptions are also diverse and evolve rapidly. In addition, there is a proliferation of schemas and standards related to metadata, resulting in a complex and moving technological landscape - hence, the need for specialized knowledge and skills in this area. The Handbook of Metadata, Semantics and Ontologies is intended as an authoritative reference for students, practitioners and researchers, serving as a roadmap for the variety of metadata schemas and ontologies available in a number of key domain areas, including culture, biology, education, healthcare, engineering and library science.

Editor

Sicilia, M.-A.

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Abstract

The aim of this book is to highlight the relationship between knowledge representation and language in artificial intelligence, and in particular on the way in which the choice of representation influences the language used to discuss a problem - and vice versa. Opening with a discussion of knowledge representation methods, and following this with a look at reasoning methods, the author begins to make his case for the intimate relationship between language and representation. He shows how each representation method fits particularly well with some reasoning methods and less so with others, using specific languages as examples. The question of representation change, an important and complex issue about which very little is known, is addressed. Dr Hodgson gathers together recent work on problem solving, showing how, in some cases, it has been possible to use representation changes to recast problems into a language that makes them easier to solve. The author maintains throughout that the relationships that this book explores lie at the heart of the construction of large systems, examining a number of the current large AI systems from the viewpoint of representation and language to prove his point.

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Abstract

A guide to database management, online searching, text retrieval, data analysis, intelligent documents and more ...

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Content

Neumaier, Sebastian (et al.): Data Integration for Open Data on the Web - Stamou, Giorgos (et al.): Ontological Query Answering over Semantic Data - Calì, Andrea: Ontology Querying: Datalog Strikes Back - Sequeda, Juan F.: Integrating Relational Databases with the Semantic Web: A Reflection - Rousset, Marie-Christine (et al.): Datalog Revisited for Reasoning in Linked Data - Kaminski, Roland (et al.): A Tutorial on Hybrid Answer Set Solving with clingo - Eiter, Thomas (et al.): Answer Set Programming with External Source Access - Lukasiewicz, Thomas: Uncertainty Reasoning for the Semantic Web - Calvanese, Diego (et al.): OBDA for Log Extraction in Process Mining

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Abstract

This book describes proven methodologies for developing semantic applications: software applications which explicitly or implicitly uses the semantics (i.e., the meaning) of a domain terminology in order to improve usability, correctness, and completeness. An example is semantic search, where synonyms and related terms are used for enriching the results of a simple text-based search. Ontologies, thesauri or controlled vocabularies are the centerpiece of semantic applications. The book includes technological and architectural best practices for corporate use.

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Abstract

This book describes efficient and effective techniques for harnessing the power of Linked Data by tackling the various aspects of managing its growing volume: storing, querying, reasoning, provenance management and benchmarking. To this end, Chapter 1 introduces the main concepts of the Semantic Web and Linked Data and provides a roadmap for the book. Next, Chapter 2 briefly presents the basic concepts underpinning Linked Data technologies that are discussed in the book. Chapter 3 then offers an overview of various techniques and systems for centrally querying RDF datasets, and Chapter 4 outlines various techniques and systems for efficiently querying large RDF datasets in distributed environments. Subsequently, Chapter 5 explores how streaming requirements are addressed in current, state-of-the-art RDF stream data processing. Chapter 6 covers performance and scaling issues of distributed RDF reasoning systems, while Chapter 7 details benchmarks for RDF query engines and instance matching systems. Chapter 8 addresses the provenance management for Linked Data and presents the different provenance models developed. Lastly, Chapter 9 offers a brief summary, highlighting and providing insights into some of the open challenges and research directions. Providing an updated overview of methods, technologies and systems related to Linked Data this book is mainly intended for students and researchers who are interested in the Linked Data domain. It enables students to gain an understanding of the foundations and underpinning technologies and standards for Linked Data, while researchers benefit from the in-depth coverage of the emerging and ongoing advances in Linked Data storing, querying, reasoning, and provenance management systems. Further, it serves as a starting point to tackle the next research challenges in the domain of Linked Data management.

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Editor

Gómez-Pérez, A. u. J. Euzenat

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Editor

Öztürk, A.

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Abstract

Three of the world's most accomplished and deep thinkers come together to explore Artificial Intelligence (AI) and the way it is transforming human society-and what this technology means for us all. An AI learned to win chess by making moves human grand masters had never conceived. Another AI discovered a new antibiotic by analyzing molecular properties human scientists did not understand. Now, AI-powered jets are defeating experienced human pilots in simulated dogfights. AI is coming online in searching, streaming, medicine, education, and many other fields and, in so doing, transforming how humans are experiencing reality. In The Age of AI, three leading thinkers have come together to consider how AI will change our relationships with knowledge, politics, and the societies in which we live. The Age of AI is an essential roadmap to our present and our future, an era unlike any that has come before. Artificial Intelligence (AI) is transforming human society in fundamental and profound ways. Not since the Age of Reason have we changed how we approach security, economics, order, and even knowledge itself. In the Age of AI, three deep and accomplished thinkers come together to consider what AI will mean for us all.

Footnote

Rez. in Spektrum der Wissenschaft 2022, H.6, S.89-90 (A. Lobe) u.d.T.: Auf dem Weg in eine neue Wissensgesellschaft.

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Abstract

This book constitutes the refereed proceedings of the joint 6th International Semantic Web Conference, ISWC 2007, and the 2nd Asian Semantic Web Conference, ASWC 2007, held in Busan, Korea, in November 2007. The 50 revised full academic papers and 12 revised application papers presented together with 5 Semantic Web Challenge papers and 12 selected doctoral consortium articles were carefully reviewed and selected from a total of 257 submitted papers to the academic track and 29 to the applications track. The papers address all current issues in the field of the semantic Web, ranging from theoretical and foundational aspects to various applied topics such as management of semantic Web data, ontologies, semantic Web architecture, social semantic Web, as well as applications of the semantic Web. Short descriptions of the top five winning applications submitted to the Semantic Web Challenge competition conclude the volume.