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 various l...
| Otros Autores: | , , |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Boca Raton :
Taylor & Francis
[2015]
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| Edición: | 1st edition |
| Colección: | Chapman & Hall/CRC machine learning & pattern recognition series.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628751706719 |
| Sumario: | 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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| Notas: | A Chapman and Hall book. |
| Descripción Física: | 1 online resource (227 p.) |
| Bibliografía: | Includes bibliographical references and index. |
| ISBN: | 9780429159480 9781482226676 |
