FIRE: knowledge-enhanced recommendation with feature interaction and intent-aware attention networks

To solve the information overload issue and enhance the user experience of various web applications, recommender systems aim to better model user interests and preferences. Knowledge Graphs (KGs), consisting of real-world objective facts and fruitful entities, play a vital role in recommender system...

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Detalles Bibliográficos
Autores principales: Zhang, Ruoyi, Ma, Huifang, Li, Qingfeng, Wang, Yike, Li, Zhixin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9734987/
https://www.ncbi.nlm.nih.gov/pubmed/36531970
http://dx.doi.org/10.1007/s10489-022-04300-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9734987/
https://www.ncbi.nlm.nih.gov/pubmed/36531970
http://dx.doi.org/10.1007/s10489-022-04300-x

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