LightFIG: simplifying and powering feature interactions via graph for recommendation

The attributes of users and items contain key information for recommendation. The latest advances demonstrate that better representations can be learned by performing graph convolutions on attribute graph of the user-item pair. Recently proposed models construct graphs that not only connect edges be...

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Detalles Bibliográficos
Autor principal: Di, Weiqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9299275/
https://www.ncbi.nlm.nih.gov/pubmed/35875639
http://dx.doi.org/10.7717/peerj-cs.1019

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9299275/
https://www.ncbi.nlm.nih.gov/pubmed/35875639
http://dx.doi.org/10.7717/peerj-cs.1019

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