Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Ningjia Qiu"'
Publikováno v:
PeerJ Computer Science, Vol 10, p e1808 (2024)
The purpose of knowledge embedding is to extract entities and relations from the knowledge graph into low-dimensional dense vectors, in order to be applied to downstream tasks, such as connection prediction and intelligent classification. Existing kn
Externí odkaz:
https://doaj.org/article/4292e3b52ba94418acd9a9f79486e8e9
Publikováno v:
Applied Sciences, Vol 13, Iss 15, p 9026 (2023)
In the prediction and modeling analysis of wear degree in the field of industrial parts processing, there are problems such as poor prediction ability for long sequence data and low sensitivity of output feedback to changes in input signals. In this
Externí odkaz:
https://doaj.org/article/61e0d6302fac490b8c92dbd79c92298b
Publikováno v:
Journal of Algorithms & Computational Technology, Vol 13 (2019)
Memory limitation and slow training speed are two important problems in sentiment analysis. In this paper, we propose a sentiment classification model based on online learning to improve the training speed of the sentiment classification. First, comb
Externí odkaz:
https://doaj.org/article/1f522eb575974fbaa9b3b661818a1a28
Publikováno v:
Journal of Algorithms & Computational Technology, Vol 12 (2018)
Noise data in text are one of the main factors affecting the quality of text categorization. A parallel noise data elimination algorithm based on principal component analysis method and term frequency-inverse document frequency method for the noise d
Externí odkaz:
https://doaj.org/article/4006a54cbb534982ac9356cd7a23c6df
Publikováno v:
Journal of Algorithms & Computational Technology, Vol 12 (2018)
This paper proposes an improved adaptive density-based spatial clustering of applications with noise (DBSCAN) algorithm based on genetic algorithm and MapReduce parallel computing programming framework to improve the poor clustering effect and low ef
Externí odkaz:
https://doaj.org/article/840622b9e6894987bcf37e2a549b7c23
Publikováno v:
Journal of Advanced Computational Intelligence and Intelligent Informatics. 24:829-836
Traffic flow prediction is one of the fundamental components in Intelligent Transportation Systems (ITS). Many traffic flow prediction models have been developed, but with limitation of noise sensitivity, which will result in poor generalization. Fus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14388165e1cb9ca560d0d4f6070b177a
https://doi.org/10.20965/jaciii.2020.p0829
https://doi.org/10.20965/jaciii.2020.p0829
Publikováno v:
2021 International Conference on Electronic Information Engineering and Computer Science (EIECS).
The classical knowledge representation model is usually based on a single triplet, however, the knowledge graph is a complex network that could not accurately represent the knowledge of knowledge graphs by just a single triplet. This paper presented
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::34d91a10b51ff1902a2b603dcdb1b4e7
https://doi.org/10.1109/eiecs53707.2021.9588072
https://doi.org/10.1109/eiecs53707.2021.9588072
Publikováno v:
Journal of Advanced Computational Intelligence and Intelligent Informatics. 23:980-989
Traditional convolutional neural networks (CNNs) use a pooling layer to reduce the dimensionality of texts, but lose semantic information. To solve this problem, this paper proposes a convolutional neural network model based on singular value decompo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff36d07a944b4fbdd6987a960fe2e4ff
https://doi.org/10.20965/jaciii.2019.p0980
https://doi.org/10.20965/jaciii.2019.p0980
Publikováno v:
Journal of Advanced Computational Intelligence and Intelligent Informatics. 23:1044-1051
In this work, we propose a multi-channel semantic fusion convolutional neural network (SFCNN) to solve the problem of emotional ambiguity caused by the change of contextual order in sentiment classification task. Firstly, the emotional tendency weigh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::46a066593086af2cb7302d4f9f0949c0
https://doi.org/10.20965/jaciii.2019.p1044
https://doi.org/10.20965/jaciii.2019.p1044
Autor:
Ningjia Qiu
Publikováno v:
International Journal of Simulation: Systems, Science & Technology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81976a22e29d26b209227c8220157883
https://doi.org/10.5013/ijssst.a.17.33.17
https://doi.org/10.5013/ijssst.a.17.33.17