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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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Date

18. 6.2018 19:22:02

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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.

Content

C H A P T E R 1 What is an ontology?; Introduction; The data deluge and information overload; Defining terms; Knowledge organization systems and ontologies; Ontologies, metadata and linked data; What can an ontology do?; Ontologies and information professionals; Alternatives to ontologies; The aims of this book; The structure of this book; C H A P T E R 2 Ontologies and the semantic web; Introduction; The semantic web and linked data; Resource Description Framework (RDF); Classes, subclasses and properties; The semantic web stack; Embedded RDF; Alternative semantic visionsLibraries and the semantic web; Other cultural heritage institutions and the semantic web; Other organizations and the semantic web; Conclusion; C H A P T E R 3 Existing ontologies; Introduction; Ontology documentation; Ontologies for representing ontologies; Ontologies for libraries; Upper ontologies; Cultural heritage data models; Ontologies for the web; Conclusion; C H A P T E R 4 Adopting ontologies; Introduction; Reusing ontologies: application profiles and data models; Identifying ontologies; The ideal ontology discovery tool; Selection criteria; Conclusion C H A P T E R 5 Building ontologiesIntroduction; Approaches to building an ontology; The twelve steps; Ontology development example: Bibliometric Metrics Ontology element set; Conclusion; C H A P T E R 6 Interrogating ontologies; Introduction; Interrogating ontologies for reuse; Interrogating a knowledge base; Understanding ontology use; Conclusion; C H A P T E R 7 The future of ontologies and the information professional; Introduction; The future of ontologies for knowledge discovery; The future role of library and information professionals; The practical development of ontologies

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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.

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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

Arguing that within the next fifty years machines will equal humans not only in reasoning power but also in their ability to perceive, interact with, and change their environment, the author describes the tremendous technological advances possible in thefield of robotics.

Content

"A dizzying display of intellect and wild imaginings by Moravec, a world-class roboticist who has himself developed clever beasts . . . Undeniably, Moravec comes across as a highly knowledgeable and creative talent-which is just what the field needs" - Kirkus Reviews.

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Footnote

Originaltitel: Machines who think: a personal inquiry into the history and prospects of artificial intelligence

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Content

Vgl. auch die Standpunkte in: Collins, H.M.: A review of Hubert Dreyfus' What computers still can't do in: Artificial intelligence 80(1996) no.1, S.99-191.

Footnote

HST und ZST werden in verschiedenen Katalogen auch in vertauschter Reihenfolge angegeben (vgl. die Gestaltung des Covers und Titelblatts). Titel des Original: What computer can't do: the limits of artificial intelligence.

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Footnote

Original u.d.T.: Apprentices of wonder

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Footnote

Originaltitel: Shadows of the mind. Rez. in: Spektrum der Wissenschaft 1996, H.8, S.118-119 (I. Diener)

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Footnote

CIR Concepts - Interactive information retrieval: Bringing the user to a selection state, von Charles Cole et al. (Montréal), konzentriert sich auf den kognitiven Aspekt von Benutzern bei der Interaktion mit den bzw. der Reaktion auf die vom IR-System ausgesandten Stimuli; "selection" bezieht sich dabei auf die Auswahl, die das System den Benutzern abverlangt und die zur Veränderung ihrer Wissensstrukturen beiträgt. - Cognitive overlaps along the polyrepresentation continuum, von Birger Larsen und Peter Ingwersen (Kopenhagen), beschreibt einen auf Ingwersens Principle of Polyrepresentation beruhenden methodischen Ansatz, der dem IR-System ein breiteres Bild des Benutzers bzw. der Dokumente vermittelt als dies bei herkömmlichen, lediglich anfragebasierten Systemen möglich ist. - Integrating approaches to relevance, von Ian Ruthven (Glasgow), analysiert den Relevanzbegriff und schlägt anstelle des gegenwärtig in IR-Systemverwendeten, eindimensionalen Relevanzkonzepts eine multidimensionale Sichtweise vor. - New cognitive directions, von Nigel Ford (Sheffield), führt neue Begriffe ein: Ford schlägt anstelle von information need und information behaviour die Alternativen knowledge need und knowledge behaviour vor.
Weitere Rez. in: JASIST 58(2007) no.5, S.758-760 (A. Gruzd): "Despite the minor drawbacks described, the book is a great source for researchers in the IR&S fields in general and in the CIR field in particular. Furthermore, different chapters of this book also might be of interest to members from other communities. For instance, librarians responsible for library instruction might find the chapter on search training by Lucas and Topi helpful in their work. Cognitive psychologists would probably be intrigued by Spink and Cole's view on multitasking. IR interface designers will likely find the chapter on KDV by Hook and Borner very beneficial. And students taking IR-related courses might find the thorough literature reviews by Ruthven and Kelly particularly useful when beginning their own research."

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Abstract

Künstliche Intelligenz ist unsere unausweichliche Zukunft. Wird sie uns ins Verderben stürzen oder zur Weiterentwicklung des Homo sapiens beitragen? Die Nobelpreis-Schmiede Massachusetts Institute of Technology ist der bedeutendste technologische Think Tank der USA. Dort arbeitet Professor Max Tegmark mit den weltweit führenden Entwicklern künstlicher Intelligenz zusammen, die ihm exklusive Einblicke in ihre Labors gewähren. Die Erkenntnisse, die er daraus zieht, sind atemberaubend und zutiefst verstörend zugleich. Neigt sich die Ära der Menschen dem Ende zu? Der Physikprofessor Max Tegmark zeigt anhand der neusten Forschung, was die Menschheit erwartet. Hier eine Auswahl möglicher Szenarien: - Eroberer: Künstliche Intelligenz übernimmt die Macht und entledigt sich der Menschheit mit Methoden, die wir noch nicht einmal verstehen. - Der versklavte Gott: Die Menschen bemächtigen sich einer superintelligenten künstlichen Intelligenz und nutzen sie, um Hochtechnologien herzustellen. - Umkehr: Der technologische Fortschritt wird radikal unterbunden und wir kehren zu einer prä-technologischen Gesellschaft im Stil der Amish zurück. - Selbstzerstörung: Superintelligenz wird nicht erreicht, weil sich die Menschheit vorher nuklear oder anders selbst vernichtet. - Egalitäres Utopia: Es gibt weder Superintelligenz noch Besitz, Menschen und kybernetische Organismen existieren friedlich nebeneinander. Max Tegmark bietet kluge und fundierte Zukunftsszenarien basierend auf seinen exklusiven Einblicken in die aktuelle Forschung zur künstlichen Intelligenz.