Predict Pairwise Trust Based on Machine Learning in Online Social Networks: A Survey

@article{Liu2018PredictPT,
  title={Predict Pairwise Trust Based on Machine Learning in Online Social Networks: A Survey},
  author={Shushu Liu and Lifang Zhang and Zheng Yan},
  journal={IEEE Access},
  year={2018},
  volume={6},
  pages={51297-51318}
}
Trust plays a crucial role in online social networks where users do not communicate or interact with each other in a direct face-to-face manner. Although many researchers have already conducted comprehensive studies on trust computing like trust evaluation, pairwise trust prediction is still relatively under explored especially with machine learning methods which can overcome the disadvantages of both linear predication and trust propagation. This survey aims to fill this gap and first provides… CONTINUE READING

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SHOWING 1-10 OF 68 REFERENCES

A Survey on Trust Evaluation in Mobile Ad Hoc Networks

  • MobiMedia
  • 2016
VIEW 13 EXCERPTS
HIGHLY INFLUENTIAL

A few useful things to know about machine learning

  • Commun. ACM
  • 2012
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Mining trust and distrust relationships in social Web applications

  • Proceedings of the 2010 IEEE 6th International Conference on Intelligent Computer Communication and Processing
  • 2010
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Novel Cost-Sensitive Approach to Improve the Multilayer Perceptron Performance on Imbalanced Data

  • IEEE Transactions on Neural Networks and Learning Systems
  • 2013
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

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