Using Stable Matching to Optimize the Balance between Accuracy and Diversity in Recommendation

Increasing aggregate diversity (or catalog coverage) is an important system-level objective in many recommendation domains where it may be desirable to mitigate the popularity bias and to improve the coverage of long-tail items in recommendations given to users. This is especially important in multistakeholder recommendation scenarios where it may be important to optimize utilities not just for the end user, but also for other stakeholders such as item sellers or producers who desire a fair representation of their items across recommendation lists produced by the system. Unfortunately, attempts to increase aggregate diversity often result in lower recommendation accuracy for end users. Thus, addressing this problem requires an approach that can effectively manage the trade-offs between accuracy and aggregate diversity. In this work, we propose a two-sided post-processing approach in which both user and item utilities are considered. Our goal is to maximize aggregate diversity while minimizing loss in recommendation accuracy. Our solution is a generalization of the Deferred Acceptance algorithm which was proposed as an efficient algorithm to solve the well-known stable matching problem. We prove that our algorithm results in a unique user-optimal stable match between items and users. Using three recommendation datasets, we empirically demonstrate the effectiveness of our approach in comparison to several baselines. In particular, our results show that the proposed solution is quite effective in increasing aggregate diversity and item-side utility while optimizing recommendation accuracy for end users

Annual Report 2019-2020

LETTER FROM THE DEAN As I write this letter wrapping up the 2019-20 academic year, we remain in a global pandemic that has profoundly altered our lives. While many things have changed, some stayed the same: our CDM community worked hard, showed up for one another, and continued to advance their respective fields. A year that began like many others changed swiftly on March 11th when the University announced that spring classes would run remotely. By March 28th, the first day of spring quarter, we had moved 500 CDM courses online thanks to the diligent work of our faculty, staff, and instructional designers. But CDM’s work went beyond the (virtual) classroom. We mobilized our makerspaces to assist in the production of personal protective equipment for Illinois healthcare workers, participated in COVID-19 research initiatives, and were inspired by the innovative ways our student groups learned to network. You can read more about our response to the COVID-19 pandemic on pgs. 17-19. Throughout the year, our students were nationally recognized for their skills and creative work while our faculty were published dozens of times and screened their films at prestigious film festivals. We added a new undergraduate Industrial Design program, opened a second makerspace on the Lincoln Park Campus, and created new opportunities for Chicago youth. I am pleased to share with you the College of Computing and Digital Media’s (CDM) 2019-20 annual report, highlighting our collective accomplishments. David MillerDeanhttps://via.library.depaul.edu/cdmannual/1003/thumbnail.jp