Computational Trust Models and Machine Learning

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Product Details

Publisher,Chapman & Hall
Publication Date,
Format, Hardcover
Weight, 453.59 g
No. of Pages, 208

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--

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