Board recommendation in Pinterest Conference Paper uri icon


  • In this paper we describe preliminary approaches for content-based recommendation of Pinterest boards to users. We describe our representation and features for Pinterest boards and users, together with a supervised recommendation model. We observe that features based on latent topics lead to better performance than features based on user-assigned Pinterest categories. We also find that using social signals (re-pins, likes, etc.) can improve recommendation quality.

author list (cited authors)

  • Kamath, K. Y., Popescu, A. M., & Caverlee, J.

editor list (cited editors)

  • Berkovsky, S., Herder, E., Lops, P., & Santos, O. C.

publication date

  • January 2013