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Published by Boca Raton: CRC Press, 2015
ISBN 10: 1482226669 ISBN 13: 9781482226669
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Published by Chapman and Hall/CRC, 2014
ISBN 10: 1482226669 ISBN 13: 9781482226669
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Published by Chapman and Hall/CRC, 2014
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Published by Chapman and Hall/CRC, 2014
ISBN 10: 1482226669 ISBN 13: 9781482226669
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Published by Apple Academic Press Inc., 2014
ISBN 10: 1482226669 ISBN 13: 9781482226669
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Published by Chapman and Hall/CRC, 2014
ISBN 10: 1482226669 ISBN 13: 9781482226669
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Published by Taylor & Francis Group, 2014
ISBN 10: 1482226669 ISBN 13: 9781482226669
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Published by Taylor & Francis Group, 2014
ISBN 10: 1482226669 ISBN 13: 9781482226669
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ISBN 10: 1482226669 ISBN 13: 9781482226669
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Buch. Condition: Neu. Computational Trust Models and Machine Learning | Xin Liu | Buch | Chapman & Hall/CRC Machine Learning & Pattern Recognition | Einband - fest (Hardcover) | Englisch | 2014 | CRC Press | EAN 9781482226669 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Language: English
Published by Taylor & Francis Inc Okt 2014, 2014
ISBN 10: 1482226669 ISBN 13: 9781482226669
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Buch. Condition: Neu. Neuware - Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various computer science areas, including multi-agent systems, online social networks, and communication systems. Identifying trust modeling challenges that cannot be addressed by traditional approaches, this book: \* Explains how reputation-based systems are used to determine trust in diverse online communities \* Describes how machine learning techniques are employed to build robust reputation systems \* Explores two distinctive approaches to determining credibility of resources-one where the human role is implicit, and one that leverages human input explicitly \* Shows how decision support can be facilitated by computational trust models \* Discusses collaborative filtering-based trust aware recommendation systems \* Defines a framework for translating a trust modeling problem into a learning problem \* Investigates the objectivity of human feedback, emphasizing the need to filter out outlying opinions Computational Trust Models and Machine Learning effectively demonstrates how novel machine learning techniques can improve the accuracy of trust assessment.
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Language: English
Published by Taylor & Francis Group, 2014
ISBN 10: 1482226669 ISBN 13: 9781482226669
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Condition: New. pp. 232 Figure This item is printed on demand.