GhostLink: Latent Network Inference for Influence-aware Recommendation

@article{Mukherjee2019GhostLinkLN,
  title={GhostLink: Latent Network Inference for Influence-aware Recommendation},
  author={Subhabrata Mukherjee and Stephan G{\"u}nnemann},
  journal={The World Wide Web Conference},
  year={2019}
}
  • Subhabrata Mukherjee, Stephan Günnemann
  • Published 2019
  • Computer Science
  • The World Wide Web Conference
  • Social influence plays a vital role in shaping a user's behavior in online communities dealing with items of fine taste like movies, food, and beer. For online recommendation, this implies that users' preferences and ratings are influenced due to other individuals. Given only time-stamped reviews of users, can we find out who-influences-whom, and characteristics of the underlying influence network? Can we use this network to improve recommendation? While prior works in social-aware… CONTINUE READING
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    References

    SHOWING 1-5 OF 5 REFERENCES
    Learning influence probabilities in social networks
    • 995
    • Highly Influential
    • PDF
    Hidden factors and hidden topics: understanding rating dimensions with review text
    • 1,075
    • Highly Influential
    • PDF
    Inferring networks of diffusion and influence
    • 978
    • Highly Influential
    • PDF
    From amateurs to connoisseurs: modeling the evolution of user expertise through online reviews
    • 302
    • Highly Influential
    • PDF
    The Author-Topic Model for Authors and Documents
    • 1,452
    • Highly Influential
    • PDF