Automated Generation and Configuration of Domain-Specific Recommender Systems
This program is tentative and subject to change.
Recommender systems (RSs) are thus powerful tools to support end-users in their respective sectors. However, the development process is challenging since it requires domain customization, which brings inefficiencies and, therefore, more development time. This work presents the development for my PhD thesis of a methodology for leveraging Model-Driven Engineering (MDE) and model-weaving techniques to facilitate the development of easily configurable RSs. This approach is intended for reuse enhancement, error reduction, and time-to-deploy reduction. The current achieved results underline the gap in the current literature and the lack of configurable support systems that RS providers need, pointing out the need for future research to develop methodologies that can treat dynamic and context-aware data effectively.
This program is tentative and subject to change.
Tue 24 SepDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
16:00 - 17:30 | |||
16:00 30mTalk | Automated Generation and Configuration of Domain-Specific Recommender Systems Doctoral Symposium A: Rickson Simioni Pereira Gran Sasso Science Institute, M: Daniel Varro Linköping University / McGill University | ||
16:30 30mTalk | AI Assisted Domain Modeling Explainability and Traceability Doctoral Symposium Jonathan Silva University of Luxembourg | ||
17:00 30mTalk | Closing & "Message from the Past" Doctoral Symposium D: Leen Lambers BTU Cottbus Senftenberg, D: Sébastien Mosser McMaster University, P: Sahar Kokaly General Motors, P: Simon Van Mierlo University of Antwerp |