This tutorial was presented at the RecSys ’22 conference, with Giacomo Balloccu, Gianni Fenu, and Mirko Marras. On the tutorial’s website, you can find the slides, the video recording of our talk, and the notebooks of the hands-on parts. The goal of this tutorial was to present the RecSys community with recent advances on explainable …
Day: August 1, 2023
Equality of Learning Opportunity via Individual Fairness in Personalized Recommendations
The formalization of the learning opportunities that should be offered by the recommendation of online courses can lead to defining what fairness means for a platform. A post-processing approach that balances personalization and equality of recommended opportunities can lead to effective and fair recommendations. In a study published by the International Journal of Artificial Intelligence …
Regulating Group Exposure for Item Providers in Recommendation
Platform owners can seek to guarantee certain levels of exposure to providers (e.g., to bring equity or to push the sales of new providers). Rendering certain groups of providers with the target exposure, beyond-accuracy objectives experience significant gains with negligible impact in recommendation utility. In a SIGIR 2022 paper, with Mirko Marras, Guilherme Ramos, and …
Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of Explanations
Being able to assess explanation quality in recommender systems and by shaping recommendation lists that account for explanation quality allows us to produce more effective recommendations. These recommendations can also increase explanation quality according to the proposed properties, fairly across demographic groups. In a SIGIR 2022 paper, with Giacomo Balloccu, Gianni Fenu, and Mirko Marras, …