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Title Computational trust models and machine learning / edited by Xin Liu, EPFL Lausanne, Switzerland, Anwitaman Datta, Nanyang Technological University Singapore, Ee-Peng Lim, Singapore Management University. [O'Reilly electronic resource]

Publication Info. Boca Raton, FL : CRC Press, [2015]
©2015
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Description 1 online resource (xxiv, 208 pages)
Series Chapman & Hall/CRC machine learning & pattern recognition series
Chapman & Hall/CRC machine learning & pattern recognition series.
Note "A Chapman & Hall book."
Summary "This book provides an introduction to computational trust models from a machine learning perspective. After reviewing traditional computational trust models, it discusses a new trend of applying formerly unused machine learning methodologies, such as supervised learning. The application of various learning algorithms, such as linear regression, matrix decomposition, and decision trees, illustrates how to translate the trust modeling problem into a (supervised) learning problem. The book also shows how novel machine learning techniques can improve the accuracy of trust assessment compared to traditional approaches"-- Provided by publisher
Bibliography Includes bibliographical references and index.
Contents 1. Introduction -- 2. Trust in online communities -- 3. Judging the veracity of claims and reliability of sources -- 4. Web credibility assessment -- 5. Trust-aware recommender systems -- 6. Biases in trust-based systems.
Subject Computational intelligence.
Machine learning.
Truthfulness and falsehood -- Mathematical models.
Intelligence informatique.
Apprentissage automatique.
Mensonge -- Modèles mathématiques.
Computational intelligence
Machine learning
Added Author Liu, Xin (Mathematician), editor.
Datta, Anwitaman, editor.
Lim, Ee-Peng, editor.
Other Form: Print version: Computational trust models and machine learning. Boca Raton : CRC Press, 2014 9781482226669 (DLC) 2014028238 (OCoLC)884440170
ISBN 9781482226676 (electronic bk.)
1482226677 (electronic bk.)
9781322637464 (MyiLibrary)
1322637466 (MyiLibrary)
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