Computational trust models and machine learning / / edited by Xin Liu, Anwitaman Datta, Ee-Peng Lim.

• Superior document: Chapman & Hall/CRC machine learning & pattern recognition series
• TeilnehmendeR: Liu, Xin (Mathematician),; Datta, Anwitaman,; Lim, Ee-Peng,
• Place / Publishing House: Boca Raton : : Taylor & Francis,, [2015]; 2015
• Year of Publication: 2015
• Language: English
• Series: Chapman & Hall/CRC machine learning & pattern recognition series.
• Physical Description: 1 online resource (227 pages) :; illustrations.
• Bibliography: Includes bibliographical references and index.
• ISBN: 9781482226669 (hardback); 9781482226676 (ebook)
• Hierarchical level: Monograph
• Statement of Responsibility: edited by Xin Liu, Anwitaman Datta, Ee-Peng Lim.

"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"--