RecSys Lab @Polimi is a research group at Politecnico di Milano working 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 meets at the ACM Recommender Systems conference.
RecSys Lab @Polimi brings together different views toward recommender systems, namely, Machine Learning and Applied Quantum 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. For more details on the activities of our research group, you may visit the website http://recsys.deib.polimi.it.
The main research areas are the following:
- Applied Quantum Machine Learning
- Recommender systems for personalization
- Performance autotuning
- Online education and knowledge tracing for student modelling
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.