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Computational Trust Models and Machine Learning

Jezik EngleskiEngleski
Knjiga Tvrdi uvez
Knjiga Computational Trust Models and Machine Learning Xin Liu
Libristo kod: 06677866
Nakladnici Apple Academic Press Inc., listopad 2014
Computational Trust Models and Machine Learning provides a detailed introduction to the concept of t... Cijeli opis
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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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Informacije o knjizi

Puni naziv Computational Trust Models and Machine Learning
Autor Xin Liu
Jezik Engleski
Uvez Knjiga - Tvrdi uvez
Datum izdanja 2014
Broj stranica 232
EAN 9781482226669
ISBN 9781482226669
Libristo kod 06677866
Nakladnici Apple Academic Press Inc.
Težina 470
Dimenzije 158 x 241 x 18

Kategorija

Computing & Information Technology > Computer science > Artificial intelligence > Machine learning
Computing & Information Technology > Computer science > Mathematical theory of computation
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