Xiangmeng Wang

Orcid: 0000-0003-3643-3353

According to our database1, Xiangmeng Wang authored at least 18 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

2020
2021
2022
2023
2024
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Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Constrained Off-policy Learning over Heterogeneous Information for Fairness-aware Recommendation.
Trans. Recomm. Syst., December, 2024

Counterfactual Explanation for Fairness in Recommendation.
ACM Trans. Inf. Syst., July, 2024

Reinforced Path Reasoning for Counterfactual Explainable Recommendation.
IEEE Trans. Knowl. Data Eng., July, 2024

Counterfactual Explainable Conversational Recommendation.
IEEE Trans. Knowl. Data Eng., June, 2024

Neural Causal Graph collaborative filtering.
Inf. Sci., 2024

Counterfactual Debasing for Multi-behavior Recommendations.
Proceedings of the Database Systems for Advanced Applications, 2024

2023
Causal Disentanglement for Semantic-Aware Intent Learning in Recommendation.
IEEE Trans. Knowl. Data Eng., October, 2023

Deconfounded recommendation via causal intervention.
Neurocomputing, April, 2023

Be Causal: De-Biasing Social Network Confounding in Recommendation.
ACM Trans. Knowl. Discov. Data, January, 2023

Causal Neural Graph Collaborative Filtering.
CoRR, 2023

2022
Reinforced Path Reasoning for Counterfactual Explainable Recommendation.
CoRR, 2022

Causal Disentanglement for Semantics-Aware Intent Learning in Recommendation.
CoRR, 2022

Off-policy Learning over Heterogeneous Information for Recommendation.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

MGPolicy: Meta Graph Enhanced Off-policy Learning for Recommendations.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Semantics-Guided Disentangled Learning for Recommendation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

2021
Be Causal: De-biasing Social Network Confounding in Recommendation.
CoRR, 2021

2020
Popularity prediction of movies: from statistical modeling to machine learning techniques.
Multim. Tools Appl., 2020

Joint Relational Dependency Learning for Sequential Recommendation.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020


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