Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Yixuan Chai"'
Publikováno v:
IEEE Access, Vol 11, Pp 82685-82695 (2023)
Extracting entities and their relationships from financial documents is crucial for analyzing and predicting future market trends. However, the current state of the art in this field faces two major challenges: multiple sentences between related enti
Externí odkaz:
https://doaj.org/article/575d2c59fa894d7eba83f680d58bf68b
Publikováno v:
Proceedings of the Institution of Civil Engineers - Water Management. 174:236-251
Concrete face rockfill dams are widely used in hydropower engineering because of their many advantages. As important structures, if the performance of the concrete face slab and the impervious curtain is weakened, leakages and even serious dam failur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::072c84455c4f96959c023d303d62dd55
https://doi.org/10.1680/jwama.20.00047
https://doi.org/10.1680/jwama.20.00047
Publikováno v:
IJCNN
Online learning can improve chatbots’ conversational abilities. Although the online learning method has enhanced the diversity of chatbots’ statements, it also brings opportunities for corruption. The chatbot may be corrupted to generate offensiv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bee0724bd51c201a76b4f2864c6b1a6f
https://doi.org/10.1109/ijcnn48605.2020.9206897
https://doi.org/10.1109/ijcnn48605.2020.9206897
Autor:
Guohua Liu, Yixuan Chai
Publikováno v:
ICTAI
Researchers have applied online deep reinforcement learning in order to enhance the open-domain conversational skills of chatbots. These chatbots have the ability to learn conversations from real users but in practical applications, some users may ta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53d1e1ddf20d3587eae93661aa7ed955
https://doi.org/10.1109/ictai.2018.00063
https://doi.org/10.1109/ictai.2018.00063
Publikováno v:
Cloud Computing and Security ISBN: 9783030000080
ICCCS (2)
ICCCS (2)
Existing Temporal Collaborative Filtering (TCF) recommendation algorithms exploit the time context to capture the user-interest drift. They have been used in the movie and music recommendation domain successfully. In online wholesale domain, e.g. Ali
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9e12d7f3b7007aaec8f94ae75d6dcc5b
https://doi.org/10.1007/978-3-030-00009-7_18
https://doi.org/10.1007/978-3-030-00009-7_18
