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Eyke Hullermeier has written 5 work(s)
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Cover for 9783642141249 Cover for 9783642140488 Cover for 9783642140549 Cover for 9783642140570 Cover for 9781402056949
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Product Description: The topic of preferences is a new branch of machine learning and data mining, and it has attracted considerable attention in artificial intelligence research in previous years. It involves learning from observations that reveal information about the preferences of an individual or a class of individuals...read more
By Johannes Furnkranz (editor) and Eyke Hullermeier (editor)

Hardcover:

9783642141249 | Springer-Verlag New York Inc, December 1, 2010, cover price $179.00 | About this edition: The topic of preferences is a new branch of machine learning and data mining, and it has attracted considerable attention in artificial intelligence research in previous years.

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Product Description: TheInternationalConferenceonInformationProcessingandManagementof- certaintyinKnowledge-BasedSystems, IPMU, isorganizedeverytwoyearswith the aim of bringing together scientists working on methods for the management of uncertainty and aggregationof information in intelligent systems...read more
By Frank Hoffmann (editor), Eyke Hullermeier (editor) and Rudolf Kruse (editor)

Paperback:

9783642140570 | Springer-Verlag New York Inc, July 12, 2010, cover price $209.00 | About this edition: TheInternationalConferenceonInformationProcessingandManagementof- certaintyinKnowledge-BasedSystems, IPMU, isorganizedeverytwoyearswith the aim of bringing together scientists working on methods for the management of uncertainty and aggregationof information in intelligent systems.

cover image for 9781402056949
Product Description: Making use of different frameworks of approximate reasoning and reasoning under uncertainty, notably probabilistic and fuzzy set-based techniques, this book develops formal models of the above inference principle, which is fundamental to CBR...read more

Hardcover:

9781402056949 | Kluwer Academic Pub, May 30, 2007, cover price $189.00 | About this edition: Making use of different frameworks of approximate reasoning and reasoning under uncertainty, notably probabilistic and fuzzy set-based techniques, this book develops formal models of the above inference principle, which is fundamental to CBR.

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