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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| Other Authors: | , , |
| Format: | eBook |
| Language: | English |
| Published: |
Boca Raton :
Taylor & Francis,
2014.
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| Series: | Chapman & Hall/CRC machine learning & pattern recognition series
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| 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"-- |
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| Physical Description: | 1 online resource. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781482226669 (hardback) 1482226669 (hardback) 9781322637464 1322637466 |