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Classifying multiclass relationships between ASes using graph convolutional network

Frontiers of Engineering Management   Pages 653-667 doi: 10.1007/s42524-022-0217-1

Abstract: We then introduce new features and propose a graph convolutional network (GCN) framework, AS-GCN, to

Keywords： autonomous system     multiclass relationship     graph convolutional network     classification algorithm     Internet    

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Efficacy of intelligent diagnosis with a dynamic uncertain causality graph model for rare disorders ofsex development

Dongping Ning, Zhan Zhang, Kun Qiu, Lin Lu, Qin Zhang, Yan Zhu, Renzhi Wang

Frontiers of Medicine 2020, Volume 14, Issue 4,   Pages 498-505 doi: 10.1007/s11684-020-0791-8

Abstract: Disorders of sex development (DSD) are a group of rare complex clinical syndromes with multiple etiologiesOn the basis of the principles and algorithms of dynamic uncertain causality graph (DUCG), a diagnosis

Keywords： disorders of sex development (DSD)     intelligent diagnosis     dynamic uncertain causality graph    

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Development of an artificial intelligence diagnostic model based on dynamic uncertain causality graph

Yang Jiao, Zhan Zhang, Ting Zhang, Wen Shi, Yan Zhu, Jie Hu, Qin Zhang

Frontiers of Medicine 2020, Volume 14, Issue 4,   Pages 488-497 doi: 10.1007/s11684-020-0762-0

Abstract: artificial intelligence (AI) diagnosis model was constructed according to the dynamic uncertain causality graph

Keywords： knowledge representation     uncertain     causality     graphical model     artificial intelligence     diagnosis     dyspnea    

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Large-scale graph processing systems: a survey Review

Ning LIU, Dong-sheng LI, Yi-ming ZHANG, Xiong-lve LI

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 3,   Pages 384-404 doi: 10.1631/FITEE.1900127

Abstract: Graph is a significant data structure that describes the relationship between entries.Many application domains in the real world are heavily dependent on graph data.However, graph applications are vastly different from traditional applications.of specific graph processing platforms.In this survey, we systematically categorize the graph workloads and applications, and provide a detailed

Keywords： Graph workloads     Graph applications     Graph processing systems    

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Detecting large-scale underwater cracks based on remote operated vehicle and graph convolutional neural

Wenxuan CAO; Junjie LI

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 11,   Pages 1378-1396 doi: 10.1007/s11709-022-0855-8

Abstract: The graph convolutional neural network (GCN) was used to segment the stitched image.

Keywords： underwater cracks     remote operated vehicle     image stitching     image segmentation     graph convolutional    

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Distributed coordination inmulti-agent systems: a graph Laplacian perspective

Zhi-min HAN,Zhi-yun LIN,Min-yue FU,Zhi-yong CHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 6,   Pages 429-448 doi: 10.1631/FITEE.1500118

Abstract: This paper reviews some main results and progress in distributed multi-agent coordination from a graphsurvey of existing literature in distributed multi-agent coordination and a new perspective in terms of graphFor different types of graph Laplacians, we summarize their inherent coordination features and specific

Keywords： Multi-agent systems     Distributed coordination     Graph Laplacian    

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Development prospact and strategic significance of tight gas and shale gas in China

Qiu Zhongjian,Zhao Wenzhi,Deng Songtao

Strategic Study of CAE 2012, Volume 14, Issue 6,   Pages 4-8

Abstract: style="text-align: justify;">Based on resource, technology and actuality, the critical factors of the developmentThe development graph from quality and types of resource and foreground of “three-step developmentThe development of tight gas and shale gas will help to improve the quality of China’s energy structure

Keywords： tight gas and shale gas     critical factors     development graph     energy security     energy structure    

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A Practical Approach to Constructing a Knowledge Graph for Cybersecurity Article

Yan Jia, Yulu Qi, Huaijun Shang, Rong Jiang, Aiping Li

Engineering 2018, Volume 4, Issue 1,   Pages 53-60 doi: 10.1016/j.eng.2018.01.004

Abstract: At present, it is very significant that certain scholars have combined the concept of the knowledge graph

Keywords： Cybersecurity     Knowledge graph     Knowledge deduction    

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Erratum to: Soft-HGRNs: soft hierarchical graph recurrent networks for multi-agent partially observable

Yixiang REN, Zhenhui YE, Yining CHEN, Xiaohong JIANG, Guanghua SONG

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 3,   Pages 480-480 doi: 10.1631/FITEE.22e0073

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A DNA Computing Model for the Graph Vertex Coloring Problem Based on a Probe Graph Article

Jin Xu, Xiaoli Qiang, Kai Zhang, Cheng Zhang, Jing Yang

Engineering 2018, Volume 4, Issue 1,   Pages 61-77 doi: 10.1016/j.eng.2018.02.011

Abstract: overcome this bottleneck and improve the processing speed, we propose a DNA computing model to solve the graphIn this article, a 3-colorable graph with 61 vertices is used to illustrate the capability of the DNAThe experiment showed that not only are all the solutions of the graph found, but also more than 99%

Keywords： DNA computing     Graph vertex coloring problem     Polymerase chain reaction    

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Stochastic extra-gradient based alternating direction methods for graph-guided regularizedminimization None

Qiang LAN, Lin-bo QIAO, Yi-jie WANG

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 6,   Pages 755-762 doi: 10.1631/FITEE.1601771

Abstract: extra-gradient alternating direction method with augmented Lagrangian function (SEGAL), to minimize the graph-guidedA number of important applications in machine learning follow the graph-guided optimization formulationWe conduct experiments on fused logistic regression and graph-guided regularized regression.

Keywords： Stochastic optimization     Graph-guided minimization     Extra-gradient method     Fused logistic regression     Graph-guided    

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Interpreting the vulnerability of power systems in cascading failures using multi-graph convolutional Research Article

Supaporn LONAPALAWONG, Changsheng CHEN, Can WANG, Wei CHEN

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12,   Pages 1848-1861 doi: 10.1631/FITEE.2200035

Abstract: system's spatial information such as the electrical distance to increase the accuracy in the process of graphuses power system topology and spatial information to optimize the edge weight assignment of the line graphThen we propose a multi-graph convolutional network (MGCN) based on a graph classification task, which

Keywords： Power systems     Vulnerability     Cascading failures     Multi-graph convolutional networks     Weighted line graph    

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Erratum to: Efficient keyword search over graph-structured data based on minimal covered Erratum

Asieh Ghanbarpour, Abbas Niknafs, Hassan Naderi,naderi@iust.ac.ir

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 6,   Pages 809-962 doi: 10.1631/FITEE.18e0133

Abstract: Unfortunately the second author’s name has been misspelt. It should be read: Abbas NIKNAFS.
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Paper evolution graph: multi-view structural retrieval for academic literature None

Dan-ping LIAO, Yun-tao QIAN

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 2,   Pages 187-205 doi: 10.1631/FITEE.1700105

Abstract: method to build structural retrieval results for academic literature, which we call a paper evolution graph

Keywords： Paper evolution graph     Academic literature retrieval     Metagraph factorization     Topic coherence    

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AI Assisted Clinical Diagnosis & Treatment, and Development Strategy

Kong Ming,He Qianfeng and Li Lanjuan

Strategic Study of CAE 2018, Volume 20, Issue 2,   Pages 86-91 doi: 10.15302/J-SSCAE-2018.02.013

Abstract: establish some basic industry standards for medical and health information, to strengthen the research and developmentof domestic medical devices, to promote the development of intelligent medical devices and smart wearable

Keywords： artificial intelligence     assisted diagnosis and treatment     knowledge graph     medical ontology     medical    

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Title Author Date Type Operation

Classifying multiclass relationships between ASes using graph convolutional network

Journal Article

Efficacy of intelligent diagnosis with a dynamic uncertain causality graph model for rare disorders ofsex development

Dongping Ning, Zhan Zhang, Kun Qiu, Lin Lu, Qin Zhang, Yan Zhu, Renzhi Wang

Journal Article

Development of an artificial intelligence diagnostic model based on dynamic uncertain causality graph

Yang Jiao, Zhan Zhang, Ting Zhang, Wen Shi, Yan Zhu, Jie Hu, Qin Zhang

Journal Article

Large-scale graph processing systems: a survey

Ning LIU, Dong-sheng LI, Yi-ming ZHANG, Xiong-lve LI

Journal Article

Detecting large-scale underwater cracks based on remote operated vehicle and graph convolutional neural

Wenxuan CAO; Junjie LI

Journal Article

Distributed coordination inmulti-agent systems: a graph Laplacian perspective

Zhi-min HAN,Zhi-yun LIN,Min-yue FU,Zhi-yong CHEN

Journal Article

Development prospact and strategic significance of tight gas and shale gas in China

Qiu Zhongjian,Zhao Wenzhi,Deng Songtao

Journal Article

A Practical Approach to Constructing a Knowledge Graph for Cybersecurity

Yan Jia, Yulu Qi, Huaijun Shang, Rong Jiang, Aiping Li

Journal Article

Erratum to: Soft-HGRNs: soft hierarchical graph recurrent networks for multi-agent partially observable

Yixiang REN, Zhenhui YE, Yining CHEN, Xiaohong JIANG, Guanghua SONG

Journal Article

A DNA Computing Model for the Graph Vertex Coloring Problem Based on a Probe Graph

Jin Xu, Xiaoli Qiang, Kai Zhang, Cheng Zhang, Jing Yang

Journal Article

Stochastic extra-gradient based alternating direction methods for graph-guided regularizedminimization

Qiang LAN, Lin-bo QIAO, Yi-jie WANG

Journal Article

Interpreting the vulnerability of power systems in cascading failures using multi-graph convolutional

Supaporn LONAPALAWONG, Changsheng CHEN, Can WANG, Wei CHEN

Journal Article

Erratum to: Efficient keyword search over graph-structured data based on minimal covered

Asieh Ghanbarpour, Abbas Niknafs, Hassan Naderi,naderi@iust.ac.ir

Journal Article

Paper evolution graph: multi-view structural retrieval for academic literature

Dan-ping LIAO, Yun-tao QIAN

Journal Article

AI Assisted Clinical Diagnosis & Treatment, and Development Strategy

Kong Ming,He Qianfeng and Li Lanjuan

Journal Article