Fridays' AI talks are digital talks on emergent AI topics, organised by MSc in Artificial Intelligence. The series consist of talks given by scientists and researchers from academia and industry AI experts, and intends to cover the wide spectrum of topics regarding artificial intelligence. We plan to organize 1 talk per month and sporadically even including panel discussions. The target audience for the Fridays' AI talks includes the current MSc in Artificial Intelligence students, our alumni, members from academia, researchers and practitioners from labs and industry.
Fridays' AI talk: Employing Social Choice Theory for Personalized and Group Recommendations
Invited speaker: Georgios Chalkiadakis, Associate Professor, School of Electrical and Computer Engineering, Technical University of Crete
Friday 16 December 2022, 18.00, Online
"In this talk, I will be describing recent research conducted in my group to tackle both the personalized and group recommendations problems, using Machine Learning and Social Choice Theory. More specifically, we build our (Bayesian) recommendation algorithms following the “you are what you consume” (Babas et al, 2013) principle, while a key novelty in our approach is the application of multiwinner voting rules to increase recommendations’ diversity and fairness.
We conduct a systematic experimental evaluation of our approaches by applying them on a real-world dataset of Points of Interest (POIs) in the popular touristic destination of Agios Nikolaos, Crete; also exploiting information collected via questionnaires from actual tourists visiting the city of Agios Nikolaos. Our experimental results (i) highlight the ability of our systems to successfully produce personalized recommendations that match the specific interests of a single user; (ii) confirm that the employment of prior knowledge regarding the preferences of tourists, based on their demographics, guides our recommender to avoid the cold-start problem; (iii) demonstrate that the use of multiwinner mechanisms allows for diverse recommendations with respect to travel-related features, and increased system performance in the case of limited user-system interactions; and (iv) show that the use of multiwinner mechanisms allows for fair group recommendations with respect to the well-known m-PROPORTIONALITY and m-ENVY-FREENESS metrics. Last but not least, our personalized Bayesian recommendation algorithm is incorporated in a real-world mobile tour-planning application for Agios Nikolaos, Crete".
Connect to attend online the talk!
Meeting ID: 868 2893 0380
Passcode: 763647
