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Abstract

Ontologies are viewed as the silver bullet for many applications, but in open or evolving systems, different parties can adopt different ontologies. This increases heterogeneity problems rather than reducing heterogeneity. This book proposes ontology matching as a solution to the problem of semantic heterogeneity, offering researchers and practitioners a uniform framework of reference to currently available work. The techniques presented apply to database schema matching, catalog integration, XML schema matching and more. Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level. Euzenat and Shvaiko's book is devoted to ontology matching as a solution to the semantic heterogeneity problem faced by computer systems. Ontology matching aims at finding correspondences between semantically related entities of different ontologies. These correspondences may stand for equivalence as well as other relations, such as consequence, subsumption, or disjointness, between ontology entities. Many different matching solutions have been proposed so far from various viewpoints, e.g., databases, information systems, artificial intelligence. With Ontology Matching, researchers and practitioners will find a reference book which presents currently available work in a uniform framework. In particular, the work and the techniques presented in this book can equally be applied to database schema matching, catalog integration, XML schema matching and other related problems. The objectives of the book include presenting (i) the state of the art and (ii) the latest research results in ontology matching by providing a detailed account of matching techniques and matching systems in a systematic way from theoretical, practical and application perspectives.

Date

20. 6.2012 19:08:22

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Abstract

Computerprogramme können menschliche Gesichter zuverlässiger erkennen als Menschen. Sie schlagen uns im Brettspiel Go, das strategisches Denken und Intuition erfordert, und sie bluffen besser als die besten Pokerspieler der Welt. Maschinen treffen komplexe Entscheidungen - oft besser und schneller als wir. Thomas Ramge erklärt sachkundig und verständlich, wie Maschinen dabei sind, das Lernen zu lernen und diskutiert die Frage: Was wird aus uns Menschen, wenn smarte Maschinen immer intelligenter werden?

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Abstract

Die künstliche Intelligenz hat in den letzten Jahrzehnten gewaltige Fortschritte gemacht. Setzt sich dieser Fortschritt in den nächsten Jahren mit der gleichen Geschwindigkeit fort, so werden unsere Personal Computer bis etwa zum Jahr 2015 die gleiche Leistungsfähigkeit wie das menschliche Gehirn erreicht haben. Die entscheidende Frage ist, ob diese Maschinen dann auch all die geistigen Fähigkeiten erwerben können, die als zutiefst menschlich empfunden werden. Im Zentrum steht dabei vor allem die Frage nach dem Bewusstsein. Gelingt es tatsächlich, Computer mit allen geistigen Fähigkeiten des Menschen auszustatten, so reicht unsere Fantasie kaum aus, die dadurch bedingten langfristigen Folgen für unsere Zivilisation vorauszusagen. Da die künstliche Intelligenz nicht den Einschränkungen des biologischen Lebens unterliegt, ist eine Entwicklung weit über die Fähigkeiten menschlicher Intelligenz hinaus denkbar. Dies schließt sogar eine potenzielle Unsterblichkeit ein - und somit den Abschied von der Wunschvorstellung, daß der Mensch die Krone der Schöpfung sei.

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Issue

Übersetzt von Adele Enders und Doris Packulat.

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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.

Footnote

Rez. in: Cataloging and classification quarterly 54(2016) no.7, S.504-505 (Claudia Horning).

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Abstract

Ontologies have been developed and investigated for quite a while now in artificial intelligente and natural language processing to facilitate knowledge sharing and reuse. More recently, the notion of ontologies has attracied attention from fields such as intelligent information integration, cooperative information systems, information retrieval, electronic commerce, and knowledge management. The author systematicaliy introduces the notion of ontologies to the non-expert reader and demonstrates in detail how to apply this conceptual framework for improved intranet retrieval of corporate information and knowledge and for enhanced Internet-based electronic commerce. In the second part of the book, the author presents a more technical view an emerging Web standards, like XML, RDF, XSL-T, or XQL, allowing for structural and semantic modeling and description of data and information.

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Abstract

Practical Ontologies for Information Professionals provides an accessible introduction and exploration of ontologies and demonstrates their value to information professionals. More data and information is being created than ever before. Ontologies, formal representations of knowledge with rich semantic relationships, have become increasingly important in the context of today's information overload and data deluge. The publishing and sharing of explicit explanations for a wide variety of conceptualizations, in a machine readable format, has the power to both improve information retrieval and discover new knowledge. Information professionals are key contributors to the development of new, and increasingly useful, ontologies. Practical Ontologies for Information Professionals provides an accessible introduction to the following: defining the concept of ontologies and why they are increasingly important to information professionals ontologies and the semantic web existing ontologies, such as RDF, RDFS, SKOS, and OWL2 adopting and building ontologies, showing how to avoid repetition of work and how to build a simple ontology interrogating ontologies for reuse the future of ontologies and the role of the information professional in their development and use. This book will be useful reading for information professionals in libraries and other cultural heritage institutions who work with digitalization projects, cataloguing and classification and information retrieval. It will also be useful to LIS students who are new to the field.

Footnote

Rez. in: Cataloging and classification quarterly 55(2017) no.6, S.413-414 (Christine DeZelar-Tiedman).