Learning Stochastic Models of Information Flow

@article{Dickens2012LearningSM,
  title={Learning Stochastic Models of Information Flow},
  author={Luke Dickens and Ian Molloy and Jorge Lobo and Pau-Chen Cheng and Alessandra Russo},
  journal={2012 IEEE 28th International Conference on Data Engineering},
  year={2012},
  pages={570-581}
}
An understanding of information flow has many applications, including for maximizing marketing impact on social media, limiting malware propagation, and managing undesired disclosure of sensitive information. This paper presents scalable methods for both learning models of information flow in networks from data, based on the Independent Cascade Model, and predicting probabilities of unseen flow from these models. Our approach is based on a principled probabilistic construction and results… CONTINUE READING
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