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Jie Long, Zihan Li, Qi Xuan, Chenbo Fu, Songtao Peng and Yong Min
The opinion recognition for comments in Internet media is a new task in text analysis. It takes comment statements as the research object, by learning the opinion tendency in the original text with annotation, and then performing opinion tendency recogni...
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Xiaochun Sun, Chenmou Wu and Shuqun Yang
With the proliferation of Knowledge Graphs (KGs), knowledge graph completion (KGC) has attracted much attention. Previous KGC methods focus on extracting shallow structural information from KGs or in combination with external knowledge, especially in com...
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Li-Na Wang, Guoqiang Zhong, Yaxin Shi and Mohamed Cheriet
Most of the dimensionality reduction algorithms assume that data are independent and identically distributed (i.i.d.). In real-world applications, however, sometimes there exist relationships between data. Some relational learning methods have been propo...
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Xinyue Lan, Liyue Wang, Cong Wang, Gang Sun, Jinzhang Feng and Miao Zhang
In this research, we introduce a deep-learning-based framework designed for the prediction of transonic flow through a linear cascade utilizing large-scale point-cloud data. In our experimental cases, the predictions demonstrate a nearly four-fold speed ...
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Sirui Shen, Daobin Zhang, Shuchao Li, Pengcheng Dong, Qing Liu, Xiaoyu Li and Zequn Zhang
Heterogeneous graph neural networks (HGNNs) deliver the powerful capability to model many complex systems in real-world scenarios by embedding rich structural and semantic information of a heterogeneous graph into low-dimensional representations. However...
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