E-BOOK
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.
Imprint Boca Raton, FL : CRC Press, [2015]
©2015

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 Internet  Electronic Book    AVAILABLE
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."
Bibliog. Includes bibliographical references and index.
Note Available only to authorized UTEP users.
Print version record.
Subject Computational intelligence.
Machine learning.
Truthfulness and falsehood -- Mathematical models.
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.
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.
Other Author Liu, Xin (Mathematician), editor.
Datta, Anwitaman, editor.
Lim, Ee-Peng, editor.
Other Title Print version: Computational trust models and machine learning. Boca Raton : CRC Press, 2014 9781482226669