Recurrent Poisson Factorization for Temporal Recommendation

4 Mar 2017Seyed Abbas HosseiniKeivan AlizadehAli KhodadadiAli ArabzadehMehrdad FarajtabarHongyuan ZhaHamid R. Rabiee

Poisson factorization is a probabilistic model of users and items for recommendation systems, where the so-called implicit consumer data is modeled by a factorized Poisson distribution. There are many variants of Poisson factorization methods who show state-of-the-art performance on real-world recommendation tasks... (read more)

PDF Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet