Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Eric Appiah Mantey"'
Publikováno v:
IEEE Access, Vol 11, Pp 40944-40953 (2023)
With the proliferation of privacy issues surrounding the Internet of Medical (IoMT) recommender system data, this study presents a Secure Recommendation and Training Technique (SERTT) which is contingent on a combination of both federated learning an
Externí odkaz:
https://doaj.org/article/51e592b0a8d746b9ae11a9ac3dbe77db
Publikováno v:
Frontiers in Public Health, Vol 10 (2022)
Blockchain is a recent revolutionary technology primarily associated with cryptocurrencies. It has many unique features including its acting as a decentralized, immutable, shared, and distributed ledger. Blockchain can store all types of data with be
Externí odkaz:
https://doaj.org/article/3fb22701be8c4858bc1bf6fcd2076e62
Autor:
Yaru Chen, Xiaohong Gu, Conghua Zhou, Xiaolong Zhu, Yi Jiang, John Kingsley Arthur, Eric Appiah Mantey, Ernest Domanaanmwi Ganaa
Publikováno v:
IEEE Access, Vol 9, Pp 7908-7920 (2021)
The matrix completion technique based on matrix factorization for recovering missing items is widely used in collaborative filtering, image restoration, and other applications. We proposed a new matrix completion model called hierarchical deep matrix
Externí odkaz:
https://doaj.org/article/3f365e77f52f4a93b4a52aa3a2aac4e9
Autor:
Eric Appiah Mantey, Conghua Zhou, Joseph Henry Anajemba, Izuchukwu M. Okpalaoguchi, Onyeachonam Dominic-Mario Chiadika
Publikováno v:
Frontiers in Public Health, Vol 9 (2021)
Recommender systems offer several advantages to hospital data management units and patients with special needs. These systems are more dependent on the extreme subtle hospital-patient data. Thus, disregarding the confidentiality of patients with spec
Externí odkaz:
https://doaj.org/article/1ebfc70ca0084a6a8fa89f9a4fcfb233
Publikováno v:
Applied Sciences, Vol 12, Iss 10, p 5202 (2022)
Recommender systems (RS) have been widely deployed in many real-world applications, but usually suffer from the long-standing user/item cold-start problem. As a promising approach, cross-domain recommendation (CDR), which has attracted a surge of int
Externí odkaz:
https://doaj.org/article/78ca4bd68dca4fc8a722073ea6835d57
Autor:
Xiaohong Gu, Yaru Chen, Conghua Zhou, Ernest Domanaanmwi Ganaa, Xiaolong Zhu, Yi Jiang, Eric Appiah Mantey, John Kingsley Arthur
Publikováno v:
IEEE Access, Vol 9, Pp 7908-7920 (2021)
The matrix completion technique based on matrix factorization for recovering missing items is widely used in collaborative filtering, image restoration, and other applications. We proposed a new matrix completion model called hierarchical deep matrix
Publikováno v:
Engineering Applications of Artificial Intelligence. 114:105132
Autor:
Izuchukwu M. Okpalaoguchi, Onyeachonam Dominic-Mario Chiadika, Eric Appiah Mantey, Joseph Henry Anajemba, Conghua Zhou
Publikováno v:
Frontiers in Public Health
Frontiers in Public Health, Vol 9 (2021)
Frontiers in Public Health, Vol 9 (2021)
Recommender systems offer several advantages to hospital data management units and patients with special needs. These systems are more dependent on the extreme subtle hospital-patient data. Thus, disregarding the confidentiality of patients with spec
Publikováno v:
ICMLC
In neighborhood rough set model, the majority rule based neighborhood classifier (NC) is easy to be misjudged with the increasing of the size of information granules. To remedy this deficiency, we propose a neighborhood collaborative classifier (NCC)