Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Ali M. Ahmed Al Sabaawi"'
Publikováno v:
PLoS ONE, Vol 15, Iss 4, p e0231457 (2020)
The development of Web 2.0 and the rapid growth of available data have led to the development of systems, such as recommendation systems (RSs), that can handle the information overload. However, RS performance is severely limited by sparsity and cold
Externí odkaz:
https://doaj.org/article/ccf2ab0fc1ba4c3e927f88613d971133
Publikováno v:
2022 International Conference on Data Science and Intelligent Computing (ICDSIC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af178304d097ceb0be3325e6013ba059
https://doi.org/10.1109/icdsic56987.2022.10076148
https://doi.org/10.1109/icdsic56987.2022.10076148
Publikováno v:
International Journal of Interactive Mobile Technologies, Vol 15, Iss 01, Pp 70-87 (2021)
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 01 (2021); pp. 70-87
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 01 (2021); pp. 70-87
*Al Sabaawi, Ali M. Ahmed (Aksaray, Yazar ) *Yenice, Yusuf Erkan (Aksaray, Yazar )
Recently, Recommender Systems (RSs) have attracted many researchers whose goal is to improve the performance of the prediction accuracy of recommendation systems
Recently, Recommender Systems (RSs) have attracted many researchers whose goal is to improve the performance of the prediction accuracy of recommendation systems
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c5dd719536dd546d1867e82784874a2
https://online-journals.org/index.php/i-jim/article/view/17751
https://online-journals.org/index.php/i-jim/article/view/17751
Recommendation systems (RSs) are tools for interacting with large and complex information spaces. They provide a personalized view of such spaces, prioritizing items likely to be of interest to the user. The main objective of RSs is to tool up users
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad982fb05f70b8a260df4c9f5e62bc72
https://avesis.gazi.edu.tr/publication/details/ebc2347d-a6b9-4e04-825c-48d9e90fd2a8/oai
https://avesis.gazi.edu.tr/publication/details/ebc2347d-a6b9-4e04-825c-48d9e90fd2a8/oai
Publikováno v:
PLoS ONE, Vol 15, Iss 4, p e0231457 (2020)
PLoS ONE
PLoS ONE
The development of Web 2.0 and the rapid growth of available data have led to the development of systems, such as recommendation systems (RSs), that can handle the information overload. However, RS performance is severely limited by sparsity and cold
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3159867b06a8361d76a7eff42c3b4ae6
https://doaj.org/article/ccf2ab0fc1ba4c3e927f88613d971133
https://doaj.org/article/ccf2ab0fc1ba4c3e927f88613d971133