Computational trust models and machine learning
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Publication
2014 - CRC Press, Boca Raton, Florida
Language
English
Word Count
52,000 words, Guess
Page Count
208 pages
Identifiers
- Internet Archiveisbn_9781482226669
- ISBN-139781482226669
- ISBN-101482226669
- Library of Congress Control Number2014028238
- OCLC Control Number894169847
and 3 more
- OCLC Control Number884440170
- Better World Books9781482226669
- Open LibraryOL31034274M
Classifications
- DDC006.3/1
- LCCQ342 .C675 2014
- LCCQ342.C675 2014
and 1 more
- LCCQ342 .C675 2015eb
Description
"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"--
Subjects
Topics
Series Statement
- Chapman & Hall/CRC machine learning & pattern recognition series
Other Editions
- Computational trust models and machine learning
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