Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Jheng-Long Wu"'
Publikováno v:
IEEE Access, Vol 8, Pp 66638-66646 (2020)
Discussion features in online communities can be effectively used to diagnose depression and allow other users or experts to provide self-help resources to those in need. Automatic emotion identification models can quickly and effectively highlight i
Externí odkaz:
https://doaj.org/article/60690229247340a68bcf5c4a2e0eddf5
Autor:
Jheng-Long Wu, Shuoyen Huang
Publikováno v:
Applied Sciences, Vol 12, Iss 21, p 10964 (2022)
Imbalanced data constitute an extensively studied problem in the field of machine learning classification because they result in poor training outcomes. Data augmentation is a method for increasing minority class diversity. In the field of text data
Externí odkaz:
https://doaj.org/article/1f51c369a1d046f39d3851d19ffa0227
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 19, Iss 1, Pp 1-12 (2019)
Abstract Background Feelings of depression can be caused by negative life events (NLE) such as the death of a family member, a quarrel with one’s spouse, job loss, or strong criticism from an authority figure. The automatic and accurate identificat
Externí odkaz:
https://doaj.org/article/7332bfcab38a4285b33a87aa56dab49e
Autor:
Jheng-Long Wu, Chiao-Yu Tang
Publikováno v:
Applied Sciences, Vol 12, Iss 7, p 3502 (2022)
Cyberbullying has become more prevalent in online social media platforms. Natural language processing and machine learning techniques have been employed to develop automatic cyberbullying detection models, which are only designed for binary classific
Externí odkaz:
https://doaj.org/article/b314e88920c742598725375d07ad321e
Autor:
Jheng-Long Wu, 吳政龍
99
During the 50 years of Japanese rule (1895-1945), the colonial government implemented a gradual assimilation policy to achieve more effective colonial rule, and thus began establishing schools all round Taiwan. Near the end of Japanese rule t
During the 50 years of Japanese rule (1895-1945), the colonial government implemented a gradual assimilation policy to achieve more effective colonial rule, and thus began establishing schools all round Taiwan. Near the end of Japanese rule t
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/e3y8w2
Autor:
Jheng-Long Wu, 吳政隆
97
Under the information times, enterprises are in order to improve the competition advantage, have to know the technical development for the market at present clearly and linking to lead enterprises, they integrate the ability that new or old t
Under the information times, enterprises are in order to improve the competition advantage, have to know the technical development for the market at present clearly and linking to lead enterprises, they integrate the ability that new or old t
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/59285415642816012305
Publikováno v:
Soft Computing. 27:8209-8222
Supervised learning applied stock prediction tasks and obtained satisfactory performance. The trading strategies are very complex and diverse but supervised learning is only learned and fitted by gold standard trading strategies. Supervised learning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c70e503644b9019e2b8eef1327e94ad
https://doi.org/10.1007/s00500-022-07716-2
https://doi.org/10.1007/s00500-022-07716-2
Autor:
Jheng-Long Wu, Wei-Yi Chung
Publikováno v:
Applied Intelligence. 52:16353-16369
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::43bc76f795e503816688eb47b94f6eb6
https://doi.org/10.1007/s10489-022-03384-9
https://doi.org/10.1007/s10489-022-03384-9
Publikováno v:
Applied Intelligence.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c02e1a8bf5d924283c8eb429eb3154ab
https://doi.org/10.1007/s10489-023-04483-x
https://doi.org/10.1007/s10489-023-04483-x
Publikováno v:
2022 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a26a56ad2b5e999e24b3bc814a4f4ad
https://doi.org/10.1109/bigdata55660.2022.10020779
https://doi.org/10.1109/bigdata55660.2022.10020779