By Xin Liu,Anwitaman Datta,Ee-Peng Lim
Computational belief types and computer Learning presents a close creation to the concept that of belief and its program in a variety of laptop technology parts, together with multi-agent platforms, on-line social networks, and communique structures. opting for belief modeling demanding situations that can't be addressed via conventional techniques, this book:
- Explains how reputation-based platforms are used to figure out belief in varied on-line communities
- Describes how computing device studying concepts are hired to construct powerful recognition systems
- Explores specified ways to settling on credibility of resources—one the place the human position is implicit, and one who leverages human enter explicitly
- Shows how selection aid may be facilitated by means of computational belief models
- Discusses collaborative filtering-based belief acutely aware suggestion systems
- Defines a framework for translating a belief modeling challenge right into a studying problem
- Investigates the objectivity of human suggestions, emphasizing the necessity to clear out outlying opinions
Computational belief versions and computer studying effectively demonstrates how novel computing device studying concepts can increase the accuracy of belief assessment.
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Additional info for Computational Trust Models and Machine Learning (Chapman & Hall/Crc Machine Learning & Pattern Recognition Series)
Computational Trust Models and Machine Learning (Chapman & Hall/Crc Machine Learning & Pattern Recognition Series) by Xin Liu,Anwitaman Datta,Ee-Peng Lim