activity
20182021
most citedTransformers with multi-modal features and post-fusion context for e-commerce session-based recommendation

9 citations · 9 across the 2 of their papers we have counts for

collaborators

5 papers

cs.IR20219 cited

Transformers with multi-modal features and post-fusion context for e-commerce session-based recommendation

Gabriel de Souza P. Moreira, Sara Rabhi, Ronay Ak +2

Session-based recommendation is an important task for e-commerce services, where a large number of users browse anonymously or may have very distinct interests for different sessio…

cs.LG2020

Hybrid Session-based News Recommendation using Recurrent Neural Networks

Gabriel de Souza P. Moreira, Dietmar Jannach, Adilson Marques da Cunha

We describe a hybrid meta-architecture -- the CHAMELEON -- for session-based news recommendation that is able to leverage a variety of information types using Recurrent Neural Netw…

cs.IR2019

On the Importance of News Content Representation in Hybrid Neural Session-based Recommender Systems

Gabriel de Souza P. Moreira, Dietmar Jannach, Adilson Marques da Cunha

News recommender systems are designed to surface relevant information for online readers by personalizing their user experiences. A particular problem in that context is that onlin…

cs.IR2019

Contextual Hybrid Session-based News Recommendation with Recurrent Neural Networks

Gabriel de Souza Pereira Moreira, Dietmar Jannach, Adilson Marques da Cunha

Recommender systems help users deal with information overload by providing tailored item suggestions to them. The recommendation of news is often considered to be challenging, sinc…

cs.IR2018

News Session-Based Recommendations using Deep Neural Networks

Gabriel de Souza P. Moreira, Felipe Ferreira, Adilson Marques da Cunha

News recommender systems are aimed to personalize users experiences and help them to discover relevant articles from a large and dynamic search space. Therefore, news domain is a c…