Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Yu-Shun Mao"'
Publikováno v:
Applied Sciences, Vol 10, Iss 7, p 2540 (2020)
Collaborative filtering recommender systems traditionally recommend products to users solely based on the given user-item rating matrix. Two main issues, data sparsity and scalability, have long been concerns. In our previous work, an approach was pr
Externí odkaz:
https://doaj.org/article/37a06d8aec8b4e689076053737c74b6d
Publikováno v:
Applied Intelligence. 53:12792-12810
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f509aa0f483227e841ac7307099c4542
https://doi.org/10.1007/s10489-022-04191-y
https://doi.org/10.1007/s10489-022-04191-y
Autor:
Yu-Shun Mao, Shie-Jue Lee
Publikováno v:
System Innovation in a Post-Pandemic World ISBN: 9781003278474
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc591a8716ffe9e9514e7af39f550d3f
https://doi.org/10.1201/9781003278474-15
https://doi.org/10.1201/9781003278474-15
Publikováno v:
Applied Sciences, Vol 10, Iss 2540, p 2540 (2020)
Applied Sciences
Volume 10
Issue 7
Applied Sciences
Volume 10
Issue 7
Collaborative filtering recommender systems traditionally recommend products to users solely based on the given user-item rating matrix. Two main issues, data sparsity and scalability, have long been concerns. In our previous work, an approach was pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a761beebcaee2a8945d1ef87c6211922
https://doi.org/10.3390/app10072540
https://doi.org/10.3390/app10072540