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Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New.

Hardcover. Zustand: Brand New. 504 pages. 9.25x7.25x1.00 inches. In Stock.

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Paperback. Zustand: Brand New. 2014 edition. 592 pages. 9.25x6.10x1.40 inches. In Stock.

Paperback. Zustand: Brand New. 2014 edition. 660 pages. 9.00x6.25x1.55 inches. In Stock.

Zustand: New. Mayank Kejriwal is Research Assistant Professor at the University of Southern California s Viterbi School of Engineering. Craig Knoblock is Executive Director of the Information Sciences Institute at the University of Southern California, where he is also R.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The two-volume set LNCS 8796 and 8797 constitutes the refereed proceedings of the 13th International Semantic Web Conference, ISWC 2014, held in Riva del Garda, in October 2014. The International Semantic Web Conference is the premier forum for Semantic Web research, where cutting edge scientific results and technological innovations are presented, where problems and solutions are discussed, and where the future of this vision is being developed. It brings together specialists in fields such as artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, human-computer interaction, natural language processing, and the social sciences. Part 1 (LNCS 8796) contains a total of 38 papers which were presented in the research track. They were carefully reviewed and selected from 180 submissions. Part 2 (LNCS 8797) contains 15 papers from the 'semantic Web in use' track which were accepted from 46 submissions. In addition, it presents 16 contributions of the RBDS track and 6 papers of the doctoral consortium.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The two-volume set LNCS 8796 and 8797 constitutes the refereed proceedings of the 13th International Semantic Web Conference, ISWC 2014, held in Riva del Garda, in October 2014. The International Semantic Web Conference is the premier forum for Semantic Web research, where cutting edge scientific results and technological innovations are presented, where problems and solutions are discussed, and where the future of this vision is being developed. It brings together specialists in fields such as artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, human-computer interaction, natural language processing, and the social sciences. Part 1 (LNCS 8796) contains a total of 38 papers which were presented in the research track. They were carefully reviewed and selected from 180 submissions. Part 2 (LNCS 8797) contains 15 papers from the 'semantic Web in use' track which were accepted from 46 submissions. In addition, it presents 16 contributions of the RBDS track and 6 papers of the doctoral consortium.

Buch. Zustand: Neu. Knowledge Graphs | Fundamentals, Techniques, and Applications | Craig Knoblock (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2021 | MIT Press Ltd | EAN 9780262045094 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

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Gebunden. Zustand: New. Generating Abstraction Hierarchies presents a completely automated approach to generating abstractions for problem solving. The abstractions are generated using a tractable, domain-independent algorithm whose only inputs are the definition of a .

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Generating Abstraction Hierarchies presents a completely automated approach to generating abstractions for problem solving. The abstractions are generated using a tractable, domain-independent algorithm whose only inputs are the definition of a problem space and the problem to be solved and whose output is an abstraction hierarchy that is tailored to the particular problem. The algorithm generates abstraction hierarchies that satisfy the `ordered monotonicity' property, which guarantees that the structure of an abstract solution is not changed in the process of refining it. An abstraction hierarchy with this property allows a problem to be decomposed such that the solution in an abstract space can be held invariant while the remaining parts of a problem are solved. The algorithm for generating abstractions is implemented in a system called ALPINE, which generates abstractions for a hierarchical version of the PRODIGY problem solver. Generating Abstraction Hierarchies formally defines this hierarchical problem solving method, shows that under certain assumptions this method can reduce the size of a search space from exponential to linear in the solution size, and describes the implementation of this method in PRODIGY. The abstractions generated by ALPINE are tested in multiple domains on large problem sets and are shown to produce shorter solutions with significantly less search than problem solving without using abstraction. Generating Abstraction Hierarchies will be of interest to researchers in machine learning, planning and problem reformation.

Buch. Zustand: Neu. Neuware - Generating Abstraction Hierarchies presents a completely automated approach to generating abstractions for problem solving. The abstractions are generated using a tractable, domain-independent algorithm whose only inputs are the definition of a problem space and the problem to be solved and whose output is an abstraction hierarchy that is tailored to the particular problem. The algorithm generates abstraction hierarchies that satisfy the `ordered monotonicity' property, which guarantees that the structure of an abstract solution is not changed in the process of refining it. An abstraction hierarchy with this property allows a problem to be decomposed such that the solution in an abstract space can be held invariant while the remaining parts of a problem are solved. The algorithm for generating abstractions is implemented in a system called ALPINE, which generates abstractions for a hierarchical version of the PRODIGY problem solver. Generating Abstraction Hierarchies formally defines this hierarchical problem solving method, shows that under certain assumptions this method can reduce the size of a search space from exponential to linear in the solution size, and describes the implementation of this method in PRODIGY. The abstractions generated by ALPINE are tested in multiple domains on large problem sets and are shown to produce shorter solutions with significantly less search than problem solving without using abstraction. Generating Abstraction Hierarchies will be of interest to researchers in machine learning, planning and problem reformation.