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"Liu, Xin (Mathematician)"
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Computational trust models and machine learning
\"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.
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Computational Trust Models and Machine Learning
This book provides a detailed introduction to the concept of trust and its application in various computer science areas. Identifying trust modeling challenges that cannot be addressed by traditional approaches, this text effectively demonstrates how novel machine learning techniques can improve the accuracy of trust assessment. It explains how reputation-based systems are used to determine trust in diverse online communities, discusses collaborative filtering-based trust aware recommendation systems, and investigates the objectivity of human feedback, emphasizing the need to filter out outlying opinions to ensure credibility.
eBook