Results 21 to 30 of about 4,990,305 (257)
Research on Accurate Recommendation of Learning Resources based on Graph Neural Networks and Convolutional Algorithms [PDF]
, 2023 In response to the challenges of learning confusion and information overload in online learning, a personalized learning resource recommendation algorithm based on graph neural networks and convolution is proposed to address the cold start and data ...
3, Yuyi, Wang, SaiNan, 1, Bozhi
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, 2021 Protein solubility is significant in producing new soluble proteins that can reduce the cost of biocatalysts or therapeutic agents. Therefore, a computational model is highly desired to accurately predict protein solubility from the amino acid sequence ...
Jianwen Chen +7 more
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A Two-Stream Graph Convolutional Neural Network for Dynamic Traffic Flow Forecasting
, 2020 Forecasting the traffic flow is a critical issue for researchers and practitioners in the field of transportation. Using the graph convolutional network (GCN) is widespread in traffic flow forecasting. Existing GCN-based methods mostly rely on undirected
Zhaoyang Li +7 more
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Word Grounded Graph Convolutional Network [PDF]
, 2023 Graph Convolutional Networks (GCNs) have shown strong performance in learning text representations for various tasks such as text classification, due to its expressive power in modeling graph structure data (e.g., a literature citation network).
Lu, Zhibin +3 more
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Dual graph convolutional neural network for predicting chemical networks
BMC Bioinformatics, 2020 Background Predicting of chemical compounds is one of the fundamental tasks in bioinformatics and chemoinformatics, because it contributes to various applications in metabolic engineering and drug discovery.
Shonosuke Harada +6 more
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Online social network user performance prediction by graph neural networks
IJAIN (International Journal of Advances in Intelligent Informatics), 2022 Online social networks provide rich information that characterizes the user’s personality, his interests, hobbies, and reflects his current state. Users of social networks publish photos, posts, videos, audio, etc. every day. Online social networks (OSN)
Fail Gafarov +2 more
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Aspect-based Sentiment Analysis Based on Dual-channel Graph Convolutional Network with Sentiment Knowledge [PDF]
Jisuanji kexue, 2023 Aspect-based sentiment analysis is a fine-grained sentiment analysis task whose goal is to classify the sentiment polarity of the given aspect terms in a sentence.Most of the current sentiment classification models build a graph neural network on the ...
YANG Ying, ZHANG Fan, LI Tianrui
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Modeling Physico-Chemical ADMET Endpoints With Multitask Graph Convolutional Networks [PDF]
, 2019 Simple physico-chemical properties like logD, solubility or serum albumin binding have a direct impact on the likelihood of success of compounds in clinical trials.
Floriane, Montanari +3 more
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PLoS ONE, 2021 Prediction of protein-ligand interactions is a critical step during the initial phase of drug discovery. We propose a novel deep-learning-based prediction model based on a graph convolutional neural network, named GraphBAR, for protein-ligand binding ...
Jeongtae Son, Dongsup Kim
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, 2022 The outbreak of COVID-19 brings almost the biggest explosions of scientific literature ever. Facing such volume literature, it is hard for researches to find desired citation when carrying out COVID-19 related research, especially for junior researchers.
Zhao, Xiangmo +5 more
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