CETD: Counterfactual Explanations by Considering Temporal Dependencies in Sequential Recommendation

CETD: Counterfactual Explanations by Considering Temporal Dependencies in Sequential Recommendation

Providing interpretable explanations can notably enhance users’ confidence and satisfaction with regard to recommender systems. Counterfactual explanations demonstrate remarkable performance in the realm of explainable sequential recommendation. However, current counterfactual explanation models des...

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Bibliographic Details
Main Authors: Ming He, Boyang An, Jiwen Wang, Hao Wen
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Applied Sciences
Subjects:
recommender systems
sequential recommendation
counterfactual explanation
Online Access:https://www.mdpi.com/2076-3417/13/20/11176

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