no code implementations • 29 Dec 2023 • Yongsu Ahn, Yu-Ru Lin
Despite the benefits of personalizing items and information tailored to users' needs, it has been found that recommender systems tend to introduce biases that favor popular items or certain categories of items, and dominant user groups.
no code implementations • 18 Nov 2023 • Yongsu Ahn, Muheng Yan, Yu-Ru Lin, Zian Wang
The escalating food insecurity in Africa, caused by factors such as war, climate change, and poverty, demonstrates the critical need for advanced early warning systems.
1 code implementation • 26 Jul 2023 • Xian Teng, Yongsu Ahn, Yu-Ru Lin
Through an expert interview and a controlled user experiment, our qualitative and quantitative results demonstrate that the proposed "de-paradox" workflow and the designed visual analytic system are effective in helping human users to identify and understand spurious associations, as well as to make accountable causal decisions.
no code implementations • 16 Mar 2023 • Yongsu Ahn, Muheng Yan, Yu-Ru Lin, Wen-Ting Chung, Rebecca Hwa
With the rise of AI and data mining techniques, group profiling and group-level analysis have been increasingly used in many domains including policy making and direct marketing.
no code implementations • 16 Mar 2023 • Yongsu Ahn, Yu-Ru Lin, Panpan Xu, Zeng Dai
Classification models learn to generalize the associations between data samples and their target classes.
1 code implementation • 1 Aug 2019 • Yongsu Ahn, Yu-Ru Lin
Data-driven decision making related to individuals has become increasingly pervasive, but the issue concerning the potential discrimination has been raised by recent studies.