Data Mining and Big Data: 7th International Conference, DMBD 2022, Beijing, China, November 21–24, 2022, Proceedings, Part I | SpringerLink
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Data Mining and Big Data

7th International Conference, DMBD 2022, Beijing, China, November 21–24, 2022, Proceedings, Part I

  • Conference proceedings
  • © 2022

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Editors:
  1. Ying Tan

    1. Peking University, Beijing, China

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  2. Yuhui Shi

    1. Southern University of Science and Technology, Shenzhen, China

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Communications in Computer and Information Science (CCIS, volume 1744)

Included in the following conference series:

Conference proceedings info: DMBD 2022.

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About this book

This two-volume set, CCIS 1744 and CCIS 1745 book constitutes the 7th International Conference, on Data Mining and Big Data, DMBD 2022, held in Beijing, China, in November 21–24, 2022.
The 62 full papers presented in this two-volume set included in this book were carefully reviewed and selected from 135 submissions. The papers present the latest research on advantages in theories, technologies, and applications in data mining and big data. The volume covers many aspects of data mining and big data as well as intelligent computing methods applied to all fields of computer science, machine learning, data mining and knowledge discovery, data science, etc.




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Table of contents (30 papers)

  1. Front Matter

    Pages i-xx
    Download chapter PDF

  2. Deep Reinforcement Learning Approach

    1. Front Matter

      Pages 1-1
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    2. Heterogeneous Multi-unit Control with Curriculum Learning for Multi-agent Reinforcement Learning

      • Jiali Chen, Kai Jiang, Rupeng Liang, Jing Wang, Shaoqiu Zheng, Ying Tan
      Pages 3-16

    3. A Deep Reinforcement Learning Approach for Cooperative Target Defense

      • Yanxue Xiong, Zhigang Wang, Liangjun Ke
      Pages 17-26

    4. Particle Swarm Based Reinforcement Learning

      • Jianyu Duan, Yanxiao Guo, Zhigang Wang, Liangjun Ke
      Pages 27-36

    5. User's Permission Reasoning Method Based on Knowledge Graph Reward Guidance Reinforcement Learning in Data Center

      • Yu Pan, Hongmei Li, Wei Li, Yi Liu, Xiang Li, Qibin Zheng et al.
      Pages 37-49

    6. SMPG: Adaptive Soft Update for Masked MADDPG

      • Yu Zhang, Shijia Zhou, Ning Guo, Tengfei Li, Xuechao Zou, Pin Tao
      Pages 50-61

    7. Attentive Relational State Representation for Intelligent Joint Operation Simulation

      • Renlong Chen, Ling Ye, Shaoqiu Zheng, Yabin Wang, Peng Cui, Ying Tan
      Pages 62-74

  3. Graph Neural Networks

    1. Front Matter

      Pages 75-75
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    2. Flow Prediction via Multi-view Spatial-Temporal Graph Neural Network

      • Shan Jiang, Qiang Wang, Chengjun Wang, Kun Liu, Shiqi Ning, Xinrun Xu
      Pages 77-92

    3. RotatSAGE: A Scalable Knowledge Graph Embedding Model Based on Translation Assumptions and Graph Neural Networks

      • Yubin Ma, Yuxin Ding, Guangbin Wang
      Pages 93-104

    4. Denoise Network Structure for User Alignment Across Networks via Graph Structure Learning

      • Li Liu, Chongyang Wang, Youmin Zhang, Ye Wang, Qun Liu, Guoyin Wang
      Pages 105-119

    5. OLPGP: An Optimized Label Propagation-Based Distributed Graph Partitioning Algorithm

      • Haoqing Ren, Bin Wu
      Pages 120-133

  4. Deep Neural Networks

    1. Front Matter

      Pages 135-135
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    2. DRGS: Low-Precision Full Quantization of Deep Neural Network with Dynamic Rounding and Gradient Scaling for Object Detection

      • Qiaojun Wu, Yuan Li, Song Chen, Yi Kang
      Pages 137-151

    3. Emotion Recognition Based on Multi-scale Convolutional Neural Network

      • Zeen Wang
      Pages 152-164

    4. Pose Sequence Model Using the Encoder-Decoder Structure for 3D Pose Estimation

      • Jiwei Zhang, Lian Yang, Tianbo Ye, Jiaen Zhou, Wendong Wang, Ying Tan
      Pages 165-177

    5. Research and Analysis of Video-Based Human Pose Estimation

      • Zheng Wang, Jing Sun, Qingxiao Xu, Kun Liu
      Pages 178-191

    6. Action Recognition for Solo-Militant Based on ResNet and Rule Matching

      • Lijing Tong, Jinzhi Feng, Huiqun Zhao, Kun Liu
      Pages 192-208

    7. Multiple Residual Quantization of Pruning

      • Yuee Zhou, HaiDong Kang, Tian Zhang, LianBo Ma, TieJun Xing
      Pages 209-219
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Other volumes

  1. Data Mining and Big Data

  2. Data Mining and Big Data

Editors and Affiliations

  • Peking University, Beijing, China

    Ying Tan

  • Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

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