GREASE: Generate Factual and Counterfactual Explanations for GNN-based Recommendations

被引：0
|
作者：
Chen, Ziheng [1 ]
Silvestri, Fabrizio [2 ]
Wang, Jia [3 ]
Zhang, Yongfeng [4 ]
Huang, Zhenhua [5 ]
Ahn, Hongshik [1 ]
Tolomei, Gabriele [2 ]
机构：
[1] Stony Brook University, Stony Brook,NY,11794, United States
[2] Sapienza University of Rome, Rome,00185, Italy
[3] The Xi’an Jiaotong-Liverpool University, Suzhou,215000, China
[4] Rutgers University, Piscataway,NJ,08854, United States
[5] South China Normal University, Guangzhou City,510631, China
来源：
arXiv | 2022年
关键词：
Compilation and indexing terms; Copyright 2024 Elsevier Inc;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Decision making - Graph neural networks - Machine learning
引用
收藏
相关论文
共 50 条
  • [1] Factual and Counterfactual Explanations in Fuzzy Classification Trees
    Fernandez, Guillermo
    Aledo, Juan A.
    Gamez, Jose Antonio
    Puerta, Jose M.
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2022, 30 (12) : 5484 - 5495
  • [2] Factual and Counterfactual Explanations for Black Box Decision Making
    Guidotti, Riccardo
    Monreale, Anna
    Giannotti, Fosca
    Pedreschi, Dino
    Ruggieri, Salvatore
    Turini, Franco
    IEEE INTELLIGENT SYSTEMS, 2019, 34 (06) : 14 - 22
  • [3] Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning
    Tan, Juntao
    Geng, Shijie
    Fu, Zuohui
    Ge, Yingqiang
    Xu, Shuyuan
    Li, Yunqi
    Zhang, Yongfeng
    PROCEEDINGS OF THE ACM WEB CONFERENCE 2022 (WWW'22), 2022, : 1018 - 1027
  • [4] GNN-based passenger request prediction
    Makhdomi, Aqsa Ashraf
    Gillani, Iqra Altaf
    TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH, 2024, 16 (10): : 1237 - 1251
  • [5] Iterative GNN-based Decoder for Question Generation
    Fei, Zichu
    Zhang, Qi
    Zhou, Yaqian
    2021 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING (EMNLP 2021), 2021, : 2573 - 2582
  • [6] USING DEEP IMAGE PRIORS TO GENERATE COUNTERFACTUAL EXPLANATIONS
    Narayanaswamy, Vivek
    Thiagarajan, Jayaraman J.
    Spanias, Andreas
    2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021), 2021, : 2770 - 2774
  • [7] On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning
    Kenny, Eoin M.
    Keane, Mark T.
    THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2021, 35 : 11575 - 11585
  • [8] Shap-enhanced counterfactual explanations for recommendations
    Zhong, Jinfeng
    Negre, Elsa
    37TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, 2022, : 1365 - 1372
  • [9] Generation and Evaluation of Factual and Counterfactual Explanations for Decision Trees and Fuzzy Rule-based Classifiers
    Stepin, Ilia
    Alonso, Jose M.
    Catala, Alejandro
    Pereira-Farina, Martin
    2020 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2020,
  • [10] A GNN-based predictor for quantum architecture search
    He, Zhimin
    Zhang, Xuefen
    Chen, Chuangtao
    Huang, Zhiming
    Zhou, Yan
    Situ, Haozhen
    QUANTUM INFORMATION PROCESSING, 2023, 22 (02)
12345