Knowledge-Aware Multispace Embedding Learning for Personalized Recommendation

Recommender systems help users filter items they may be interested in from massive multimedia content to alleviate information overload. Collaborative filtering-based models perform recommendation relying on users’ historical interactions, which meets great difficulty in modeling users’ interests wi...

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Detalles Bibliográficos
Autores principales: Jian, Meng, Zhang, Chenlin, Fu, Xin, Wu, Lifang, Wang, Zhangquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8954710/
https://www.ncbi.nlm.nih.gov/pubmed/35336383
http://dx.doi.org/10.3390/s22062212

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8954710/
https://www.ncbi.nlm.nih.gov/pubmed/35336383
http://dx.doi.org/10.3390/s22062212

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