RecSys@Polimi is a research group at Politecnico di Milano that researches on the next generation of smart technologies with particular application in Recommender Systems. The group is part of the RecSys community, which is an international forum who annually meet at RecSys conference.
RecSys@Polimi brings together the different views toward recommender systems, namely, Machine Learning, Signal Processing, Human Computer Interaction, Psychology, and Aesthetics, by incorporating these different disciplines to develop new ideas that ultimately lead to new recommender systems.
There are several lines of research, currently pursued by RecSys@Polimi group, mostly within the field of recommender systems but also including performance autotuning and applied quantum machine learning. See the People page for more information.
NEWS: Amazon Personalize, a machine learning service that provides recommendation models, has added Hierarchical Recurrent Neural Network (HRNN), which our research group contributed to develop. For more details see the article and Amazon HRNN documentation.
NEWS: Our paper “A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research” has been published on ACM TOIS!