Computational trust models and machine learning
By: editors, Xin Liu, Anwitaman Datta, Ee-Peng Lim
Series: Chapman & Hall/CRC machine learning & pattern recognition series
Publisher: Taylor & Francis; CRC Press
Published: 2014
Place of publication: Boca Raton
Language: eng
Number of pages: 208
ISBN-13: 9781482226669
Subjects: Computational intelligence; Machine learning; Truthfulness and falsehood; Mathematical models; COMPUTERS / Machine Theory; COMPUTERS / Software Development & Engineering / Systems Analysis & Design; TECHNOLOGY & ENGINEERING / Electronics / General
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"--
Notes: Includes bibliographical references and index.