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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Detalhes bibliográficos

Principais autores:	Ming He, Boyang An, Jiwen Wang, Hao Wen
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2023-10-01
Colecção:	Applied Sciences
Assuntos:	recommender systems sequential recommendation counterfactual explanation
Acesso em linha:	https://www.mdpi.com/2076-3417/13/20/11176
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