Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Jangmin Oh"'
Autor:
Jangmin Oh
Publikováno v:
IEEE Access, Vol 12, Pp 122695-122701 (2024)
This study proposes a cost-effective method for developing a model that extracts actual product names from order item descriptions in food delivery requests processed by a delivery agency platform. First, we utilize GPT-4, a state-of-the-art generati
Externí odkaz:
https://doaj.org/article/1a42c1e2125547b6911d26cacfa1ec43
Autor:
Minseo Park, Jangmin Oh
Publikováno v:
Applied Sciences, Vol 14, Iss 16, p 7255 (2024)
This study proposes how to incorporate concurrent purchase data into e-commerce recommendation systems to improve their predictive accuracy. We identified that concurrent purchases account for about 23% of total orders on Katcher’s, a Korean e-comm
Externí odkaz:
https://doaj.org/article/579d80ac9cfb4d1ab48c2150ea9c8909
Autor:
Jangmin Oh
Publikováno v:
PeerJ Computer Science, Vol 8, p e915 (2022)
This paper proposes a pattern-based stock trading system using ANN-based deep learning and utilizing the results to analyze and forecast highly volatile stock price patterns. Three highly volatile price patterns containing at least a record of the pr
Externí odkaz:
https://doaj.org/article/abf3c3b4b45c4549ad4df8fd56538632
Autor:
Jangmin OH
Publikováno v:
IEICE Transactions on Information and Systems. :1431-1442
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::662d7e18dfb514bd0fc5dd3915e1e25f
https://doi.org/10.1587/transinf.2021edp7243
https://doi.org/10.1587/transinf.2021edp7243
Autor:
Jangmin Oh
Publikováno v:
PeerJ. Computer science. 8
This paper proposes a pattern-based stock trading system using ANN-based deep learning and utilizing the results to analyze and forecast highly volatile stock price patterns. Three highly volatile price patterns containing at least a record of the pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c808fee2d6d19bfe0b71a3946c299619
https://pubmed.ncbi.nlm.nih.gov/35494871
https://pubmed.ncbi.nlm.nih.gov/35494871