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DyGKT: Dynamic Graph Learning for Knowledge Tracing Conference paper
KE CHENG, LINZHI PENG, PENGYANG WANG, JUNCHEN YE, LEILEI SUN, BOWEN DU. DyGKT: Dynamic Graph Learning for Knowledge Tracing[C], New York, NY, USA:Association for Computing Machinery, 2024, 409-420.
Authors:  KE CHENG;  LINZHI PENG;  PENGYANG WANG;  JUNCHEN YE;  LEILEI SUN; et al.
Favorite | TC[Scopus]:1 | Submit date：2024/08/28
Dynamic Graph  Educational Data Mining  Graph Neural Networks  Knowledge Tracing  
Derm: SLA-aware Resource Management for Highly Dynamic Microservices Conference paper
Chen Liao, Shutian Luo, Chenyu Lin, Zizhao Mo, XU HUANLE, Kejiang Ye, Chengzhong Xu. Derm: SLA-aware Resource Management for Highly Dynamic Microservices[C]:Institute of Electrical and Electronics Engineers Inc., 2024.
Authors:  Chen Liao;  Shutian Luo;  Chenyu Lin;  Zizhao Mo;  XU HUANLE; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2024/08/23
Dynamic Microservice Graph  Resource Scaling  Uncertainty  
Multi-view dynamic graph convolution neural network for traffic flow prediction Journal article
Huang,Xiaohui, Ye,Yuming, Yang,Xiaofei, Xiong,Liyan. Multi-view dynamic graph convolution neural network for traffic flow prediction[J]. Expert Systems with Applications, 2023, 222, 119779.
Authors:  Huang,Xiaohui;  Ye,Yuming;  Yang,Xiaofei;  Xiong,Liyan
Favorite | TC[WOS]:25 TC[Scopus]:27  IF:7.5/7.6 | Submit date：2023/08/03
Dynamic Fusion  Graph Convolution Network  Multi-view Encoder–decoders  Traffic Flow Prediction  
Streaming Graph Embeddings via Incremental Neighborhood Sketching Journal article
Yang, Dingqi, Qu, Bingqing, Yang, Jie, Wang, Liang, Cudre-Mauroux, Philippe. Streaming Graph Embeddings via Incremental Neighborhood Sketching[J]. IEEE Transactions on Knowledge and Data Engineering, 2023, 35(5), 5296-5310.
Authors:  Yang, Dingqi;  Qu, Bingqing;  Yang, Jie;  Wang, Liang;  Cudre-Mauroux, Philippe
Favorite | TC[WOS]:3 TC[Scopus]:4  IF:8.9/8.8 | Submit date：2022/05/17
Dynamic Graph Embedding  Streaming Graph  Concept Drift  Data Sketching  Consistent Weighted Sampling  
A graph-attention based spatial-temporal learning framework for tourism demand forecasting Journal article
Zhou, Binggui, Dong, Yunxuan, Yang, Guanghua, Hou, Fen, Hu, Zheng, Xu, Suxiu, Ma, Shaodan. A graph-attention based spatial-temporal learning framework for tourism demand forecasting[J]. Knowledge-Based Systems, 2023, 263, 110275.
Authors:  Zhou, Binggui;  Dong, Yunxuan;  Yang, Guanghua;  Hou, Fen;  Hu, Zheng; et al.
Favorite | TC[WOS]:6 TC[Scopus]:8  IF:7.2/7.4 | Submit date：2023/04/03
Tourism Demand Forecasting  Dynamic Spatial Connections  Spatial-temporal Learning  Graph Neural Network  Attention Mechanism  
Multi-Aspect Embedding of Dynamic Graphs Conference paper
Sun, Aimin, Gong, Zhiguo. Multi-Aspect Embedding of Dynamic Graphs[C]. Mohammad Al Hasan, Li Xiong, New York, NY, United States:Association for Computing Machinery, 2022, 4520-4524.
Authors:  Sun, Aimin;  Gong, Zhiguo
Favorite | TC[WOS]:0 TC[Scopus]:1 | Submit date：2022/11/07
Graph Embedding  Dynamic Graph  Multi-aspect  
Dgcb-net: Dynamic graph convolutional broad network for 3d object recognition in point cloud Journal article
Tian,Yifei, Chen,Long, Song,Wei, Sung,Yunsick, Woo,Sangchul. Dgcb-net: Dynamic graph convolutional broad network for 3d object recognition in point cloud[J]. Remote Sensing, 2021, 13(1), 1-20.
Authors:  Tian,Yifei;  Chen,Long;  Song,Wei;  Sung,Yunsick;  Woo,Sangchul
Favorite | TC[WOS]:9 TC[Scopus]:10  IF:4.2/4.9 | Submit date：2021/03/09
3d Object Recognition  Broad Learning System  Dynamic Graph Convolution  Point Cloud Analysis