Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Meshal Alfarhood"'
Autor:
Sultan Alfarhood, Meshal Alfarhood
Publikováno v:
Alexandria Engineering Journal, Vol 100, Iss , Pp 53-60 (2024)
The primary goal of recommender systems is to identify and propose items that users might find appealing. A large number of these systems are heavily dependent on explicit interactions between the user and the item, which can often be infrequent. In
Externí odkaz:
https://doaj.org/article/ae48b01a15364130b0afbb50dc7caab6
Autor:
Meshal Alfarhood, Rakan Alotaibi, Bassam Abdulrahim, Ahmad Einieh, Mohammed Almousa, Abdulrhman Alkhanifer
Publikováno v:
International Journal of Aerospace Engineering, Vol 2024 (2024)
Flight delays are a major concern for both travelers and airlines, with significant financial and reputational consequences. Accurately predicting flight delays is crucial for enhancing customer satisfaction and airline revenues. In this paper, we le
Externí odkaz:
https://doaj.org/article/f672153cace949acbb0af43d926912e8
Publikováno v:
Applied Sciences, Vol 13, Iss 14, p 8192 (2023)
Image-based Arabian camel breed classification is an important task for various practical applications, such as breeding management, genetic improvement, conservation, and traceability. However, it is a challenging task due to the lack of standardize
Externí odkaz:
https://doaj.org/article/650864f9d1f34f019a34fe86d31851b0
Autor:
Meshal Alfarhood, Jianlin Cheng
Publikováno v:
IEEE Access, Vol 8, Pp 183633-183648 (2020)
Matrix Factorization (MF) method is widely popular for personalized recommendations. However, the natural data sparsity problem limits its performance, where users generally only interact with a small fraction of available items. Accordingly, several
Externí odkaz:
https://doaj.org/article/c30d989d2ec840da9efbb71f606e3df4
Autor:
Jianlin Cheng, Meshal Alfarhood
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9789811567582
The term “information overload” has gained popularity over the last few years. It defines the difficulties people face in finding what they want from a huge volume of available information. Recommender systems have been recognized to be an effect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56b6c92e2c3a538548106dfe6d12feff
https://doi.org/10.1007/978-981-15-6759-9_1
https://doi.org/10.1007/978-981-15-6759-9_1
Autor:
Jianlin Cheng, Meshal Alfarhood
Recommender systems today have become an essential component of any commercial website. Collaborative filtering approaches, and Matrix Factorization (MF) techniques in particular, are widely used in recommender systems. However, the natural data spar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::336f58494c40baec8c6ecad7c809eae8
Autor:
Jianlin Cheng, Meshal Alfarhood
Publikováno v:
ICMLA
Matrix Factorization (MF) is a successful collaborative filtering approach used in recommendation systems. However, its performance decreases significantly when users of the system have limited, inadequate feedback data. This problem is also known as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac799c7123c720cadcaf78951fbce1c6
https://doi.org/10.1109/icmla.2019.00034
https://doi.org/10.1109/icmla.2019.00034
Autor:
Mauro Lemus, Jon Patman, Kannappan Palaniappan, Soliman Islam, Prasad Calyam, Meshal Alfarhood
Publikováno v:
INFOCOM Workshops
Fog computing is a rapidly emerging paradigm concerned with providing energy- and latency-aware solutions to users by moving computing and storage capabilities closer to end users via fog networks. A major challenge associated with such a goal is ens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e9020ff98eea4aa66d63c8132bf71f4
https://doi.org/10.1109/infcomw.2018.8407027
https://doi.org/10.1109/infcomw.2018.8407027