Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Thi-Ngan Pham"'
Publikováno v:
The Journal of Asian Finance, Economics and Business. 7:275-281
Publikováno v:
International Journal of Information Systems and Supply Chain Management. 13:59-76
The purpose of this article is to determine the safety stock for an omni-channel environment. The “Square Root Law” (for centralization of storage facilities) was proposed to combine the safety stock for both online and offline channels. A simula
Autor:
Thanh-Huyen Pham, Van-Tuan Phan, Thi-Ngan Pham, Thi-Hong Vuong, Tri-Thanh Nguyen, Quang-Thuy Ha
Publikováno v:
Recent Challenges in Intelligent Information and Database Systems ISBN: 9789811982330
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8860a6ce62ec91ca393cf5b43ceb6615
https://doi.org/10.1007/978-981-19-8234-7_36
https://doi.org/10.1007/978-981-19-8234-7_36
Publikováno v:
Sustainability; Volume 14; Issue 14; Pages: 8354
A plethora of present studies has the purpose of analyzing the connection related to the effect of environmental, social, and governance (ESG) on business performance. However, it has still not been able to bring out comprehensive results because of
Publikováno v:
Recent Challenges in Intelligent Information and Database Systems ISBN: 9789811616846
ACIIDS (Companion)
ACIIDS (Companion)
Covering based rough set is an important extension of Pawlak's traditional rough set. Reduction is a typical application of rough sets, including traditional, covering based and other rough set extensions. Although this task has several proposals, it
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2aa99b1d7575eaea2842628bfd7e4c47
https://doi.org/10.1007/978-981-16-1685-3_5
https://doi.org/10.1007/978-981-16-1685-3_5
Autor:
Thi-Ngan Pham, Thi-Cham Nguyen, Hong-Nhung Bui, Quang-Thuy Ha, Hoang-Quynh Le, Tri-Thanh Nguyen
Publikováno v:
KSE
Recently, deep Convolutional Neural Network (CNN) model has achieved remarkable results in Natural Language Processing (NLP) tasks, such as information retrieval, relation classification, semantic parsing, sentence modeling and other traditional NLP
A Lifelong Sentiment Classification Framework Based on a Close Domain Lifelong Topic Modeling Method
Publikováno v:
Intelligent Information and Database Systems ISBN: 9783030419639
ACIIDS (1)
ACIIDS (1)
In lifelong machine learning, the determination of the hypotheses related to the current task is very meaningful thanks to the reduction of the space to look for the knowledge patterns supporting for solving the current task. However, there are few s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3412e9df93fc5485a769a3b560d70901
https://doi.org/10.1007/978-3-030-41964-6_50
https://doi.org/10.1007/978-3-030-41964-6_50
Publikováno v:
Advanced Computational Methods for Knowledge Engineering ISBN: 9783030383633
ICCSAMA
ICCSAMA
Lifelong machine learning has recently become a hot topic attracting the researchers all over the world by its effectiveness in dealing with current problem by exploiting the past knowledge. The combination of topic modeling on previous domain knowle
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57b06370da7fc4a22224ef6a726257fe
https://doi.org/10.1007/978-3-030-38364-0_13
https://doi.org/10.1007/978-3-030-38364-0_13
Publikováno v:
Journal of Information and Telecommunication. 1:141-154
Multi-label classification (MLC) has drawn much attention, thanks to its usefulness and omnipresence in real-world applications in which objects may be characterized by more than one label as in the traditional approach. Getting multi-label examples
Autor:
Quang-Thuy Ha, Thi-Ngan Pham, Thi-Cham Nguyen, Minh-Tuoi Tran, Tri-Thanh Nguyen, Van-Quang Nguyen, Thi-Hong Vuong
Publikováno v:
Intelligent Information and Database Systems ISBN: 9783319754161
ACIIDS (1)
ACIIDS (1)
Lifelong machine learning is emerging in recent years thanks to its ability to use past knowledge for current problem. Lifelong topic modeling algorithms, such as LTM and AMC, are proposed and they are very useful. However, these algorithms focus on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56913c45c50bef512dea6e3c64029361
https://doi.org/10.1007/978-3-319-75417-8_19
https://doi.org/10.1007/978-3-319-75417-8_19