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"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…

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Editions

5 editions
  • Other · English · 2020
    Taylor & Francis Group · 9780367739331
  • Other · English · 2014
    Taylor & Francis Group · 232 pages · 9780429159480
  • Other · English · 2014
    Taylor & Francis Group · 232 pages · 9781482226676
  • Other · English · 2014
    Taylor & Francis · 208 pages · 9781482226669
  • Other · English · 2014
    Taylor & Francis Group · 227 pages · 9781322637464
Computational intelligenceMachine learningTruthfulness and falsehoodMathematical modelsCOMPUTERS / Machine TheoryIntelligence informatiqueApprentissage automatiqueMensonge