9 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.IR2023
Fast and Examination-agnostic Reciprocal Recommendation in Matching Markets
Yoji Tomita, Riku Togashi, Yuriko Hashizume +1
In matching markets such as job posting and online dating platforms, the recommender system plays a critical role in the success of the platform. Unlike standard recommender system…
cs.IR2023★ 1 cited
A Critical Reexamination of Intra-List Distance and Dispersion
Naoto Ohsaka, Riku Togashi
Diversification of recommendation results is a promising approach for coping with the uncertainty associated with users' information needs. Of particular importance in diversified…
cs.IR2023★ 9 cited
Curse of "Low" Dimensionality in Recommender Systems
Naoto Ohsaka, Riku Togashi
Beyond accuracy, there are a variety of aspects to the quality of recommender systems, such as diversity, fairness, and robustness. We argue that many of the prevalent problems in…