no code implementations • CVPR 2023 • Siwon Kim, Jinoh Oh, Sungjin Lee, Seunghak Yu, Jaeyoung Do, Tara Taghavi
In this paper, we propose counterfactual explanation with text-driven concepts (CounTEX), where the concepts are defined only from text by leveraging a pre-trained multi-modal joint embedding space without additional concept-annotated datasets.
no code implementations • 18 Aug 2022 • Minseok Kim, Jinoh Oh, Jaeyoung Do, Sungjin Lee
Graph neural networks (GNNs) have achieved remarkable success in recommender systems by representing users and items based on their historical interactions.
no code implementations • 28 Jul 2022 • Hongyu Shen, Jinoh Oh, Shuai Zhao, Guoyin Wang, Tara Taghavi, Sungjin Lee
Then we propose a graph convolutional network(GCN) based model, namely Personalized Dynamic Routing Feature Encoder(PDRFE), that generates personalized customer representations learned from the built graph.
1 code implementation • RecSys 2016 • Donghyun Kim, Chanyoung Park, Jinoh Oh, Sungyoung Lee, Hwanjo Y
However, due to the inherent limitation of the bag-of-words model, they have difficulties in effectively utilizing contextual information of the documents, which leads to shallow understanding of the documents.