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Heri Ramampiaro

2017

Content-Based Social Recommendation with Poisson Matrix Factorization

·267 words
Eliezer De Souza Da Silva Helge Langseth Heri Ramampiaro Publication Conference ECML Bayesian Matrix Factorization Recommender Systems Variational Inference

A latent variable probabilistic model for recommender systems that combines social trust, item content, and user preferences into a unified Poisson matrix factorization framework. This model jointly factorizes the user–item interaction matrix and item–content matrix, accounting for social relationships and content information to enhance recommendation accuracy.