The proceedings of the accepted papers can be found here.
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Keynote Speaker:
Keynote Speaker:
Prof. Dietmar Jannach
Dietmar Jannach is a professor of computer science at the University of Klagenfurt, Austria. His main research theme is related to the application of intelligent system technology to practical problems and the development of methods for building knowledge-intensive software applications. In recent years, he worked on various topics in the area of recommender systems. In this area, he also published the first international textbook on the topic.
Title: Multi-Objective Recommendation: Overview and Challenges
Abstract
It is well known from the literature that optimizing recommendations for a single objective, e.g., prediction accuracy, may be too limiting in certain applications. Instead, it is often important not only to consider multiple quality factors of recommendations, e.g., diversity, but to also take the perspectives of multiple stakeholders into account. In this talk, we will review different approaches from the literature that aim to consider multiple objectives in the recommendation process. Furthermore, we will outline open challenges and future directions in this area.
Program (September 23)
Program (September 23)
SESSION 1 (9:00-10:30)
SESSION 1 (9:00-10:30)
9:00-9:05 Introduction
9:05-9:55 Dietmar Jannach (Keynote)
Multi-Objective Recommendation: Overview and Challenges
9:55-10:15 Sinan Seymen, Anna-Lena Sachs and Edward Malthouse
Making smart recommendations for perishable and stockout products (long)
10:15-10:30 Yiding Ran, Hengchang Hu and Min-Yen Kan
PM K-LightGCN: Optimizing for Accuracy and Popularity Match in Course Recommendation (short)
BREAK (10:30-11:00)
BREAK (10:30-11:00)
SESSION 2 (11:00-12:05)
SESSION 2 (11:00-12:05)
11:00-11:20 Chunpai Wang, Shaghayegh Sahebi and Peter Brusilovsky
Proximity-Based Educational Recommendations: A Multi-Objective Framework (long)
11:20-11:35 Oleg Lesota, Stefan Brandl, Matthias Wenzel, Alessandro Benedetto Melchiorre, Elisabeth Lex, Navid Rekabsaz and Markus Schedl
Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization (short)
11:35-11:50 Peter Knees, Andres Ferraro and Moritz Hübler
Bias and Feedback Loops in Music Recommendation: Studies on Record Label Impact (short)
11:50-12:05 Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara, Daniele Malitesta and Claudio Pomo
How Neighborhood Exploration influences Novelty and Diversity in Graph Collaborative Filtering (short)
Poster Session (12:05 -- 12:30)
Poster Session (12:05 -- 12:30)
Tahereh Arabghalizi and Alexandros Labrinidis
A Ranked Bandit Approach for Multi-stakeholder Recommender Systems
Mounir Hafsa, Pamela Wattebled, Julie Jacques and Laetitia Jourdan
A Multi-Objective E-learning Recommender System at Mandarine Academy
Renata Pelissari, Paulo Alencar, Sarah Ben Amor and Leonardo Tomazeli Duarte
A systematic review of the use of multiple criteria decision aiding methods in recommender systems: preliminary results
Yan Zhao, Mitchell Goodman, Sameer Kanase, Shenghe Xu, Yannick Kimmel, Brent Payne, Saad Khan and Patricia Grao
Mitigating Targeting Bias in Content Recommendation with Causal Bandits
Recorded video of MORS 2022 workshop
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