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 var...

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Bibliographic Details
Other Authors: Liu, Xin (Editor), Datta, Anwitaman (Editor), Lim, Ee-Peng (Editor)
Format: Electronic eBook
Language:English
Published: Boca Raton, FL CRC Press [2015]
Series:Chapman & Hall/CRC machine learning & pattern recognition series
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Links:https://learning.oreilly.com/library/view/-/9781482226669/?ar
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"--
Item Description:"A Chapman & Hall book.". - Includes bibliographical references and index. - Print version record
Physical Description:1 Online-Ressource (xxiv, 208 Seiten)
ISBN:9781482226676
1482226677
9781322637464
1322637466
9781482226669