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Recommender Systems

2019

Time is of the Essence: a Joint Hierarchical RNN and Point Process Model for Time and Item Predictions

·272 words
Bjørnar Vassøy Massimiliano Ruocco Eliezer De Souza Da Silva Erlend Aune Publication Conference WSDM Point Processes Recurrent Neural Networks Recommender Systems

A joint model combining a Hierarchical RNN for session-based recommendations and a Point Process model for predicting return times. This approach improves both recommendation accuracy and return-time predictions over strong baselines.

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.