Board recommendation in Pinterest Conference Paper uri icon

abstract

  • 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.

name of conference

  • Late-Breaking Results, Project Papers and Workshop Proceedings of the 21st Conference on User Modeling, Adaptation, and Personalization., Rome, Italy, June 10-14, 2013

published proceedings

  • CEUR Workshop Proceedings

author list (cited authors)

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

complete list of authors

  • Kamath, KY||Popescu, AM||Caverlee, J

editor list (cited editors)

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

publication date

  • January 2013