Computational Trust Models and Machine Learning

<p><strong>Computational Trust Models and Machine Learning</strong> provides a detailed introduction to the concept of trust and its application in various computer science areas including multi-agent systems online social networks and communication systems. Identifying trust modeling challenges that cannot be addressed by traditional approaches this book:</p><p></p><ul> <br><br><li>Explains how reputation-based systems are used to determine trust in diverse online communities</li> <br><br><li>Describes how machine learning techniques are employed to build robust reputation systems</li> <br><br><li>Explores two distinctive approaches to determining credibility of resources—one where the human role is implicit and one that leverages human input explicitly</li> <br><br><li>Shows how decision support can be facilitated by computational trust models</li> <br><br><li>Discusses collaborative filtering-based trust aware recommendation systems</li> <br><br><li>Defines a framework for translating a trust modeling problem into a learning problem</li> <br><br><li>Investigates the objectivity of human feedback emphasizing the need to filter out outlying opinions</li> </ul><p></p><p><b>Computational Trust Models and Machine Learning </b>effectively demonstrates how novel machine learning techniques can improve the accuracy of trust assessment.</p>