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Database Systems for Advanced Applications

28th International Conference, DASFAA 2023, Tianjin, China, April 17–20, 2023, Proceedings, Part IV

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Xin Wang

    1. Tianjin University, Tianjin, China

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  2. Maria Luisa Sapino

    1. University of Torino, Turin, Italy

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  3. Wook-Shin Han

    1. POSTECH, Pohang, Korea (Republic of)

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  4. Amr El Abbadi

    1. University of California Santa Barbara, Santa Barbara, USA

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  5. Gill Dobbie

    1. University of Auckland, Auckland, New Zealand

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  6. Zhiyong Feng

    1. Tianjin University, Tianjin, China

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  7. Yingxiao Shao

    1. Beijing University of Posts and Telecommunications, Beijing, China

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  8. Hongzhi Yin

    1. The University of Queensland, Brisbane, Australia

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13946)

Included in the following conference series:

Conference proceedings info: DASFAA 2023.

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Table of contents (67 papers)

  1. Front Matter

    Pages i-xxvii
    Download chapter PDF

  2. Applications of Machine Learning

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Event Relation Extraction Using Type-Guided Attentive Graph Convolutional Networks

      • Ling Zhuang, Po Hu, Weizhong Zhao
      Pages 3-20

    3. PMJEE: A Prototype Matching Framework for Joint Event Extraction

      • Haochen Li, Tong Mo, Di Geng, Weiping Li
      Pages 21-36

    4. Storyline Generation from News Articles Based on Approximate Personalized Propagation of Neural Predictions

      • Junli Wang, Xujian Zhao, Peiquan Jin, Chunming Yang, Bo Li, Hui Zhang
      Pages 37-52

    5. Broaden Your Horizons: Inter-news Relation Mining for Fake News Detection

      • Lei Zhang, Hongbo Xu, Fengzhao Shi, Chaoyang Yan, Yongxiu Xu
      Pages 53-62

    6. Cost-Effective Clustering by Aggregating Local Density Peaks

      • Wen-Bo Xie, Bin Chen, Jun-Hao Shi, Yan-Li Lee, Xin Wang, Xun Fu
      Pages 63-73

    7. Enlarge the Hidden Distance: A More Distinctive Embedding to Tell Apart Unknowns for Few-Shot Learning

      • Zhaochen Li, Kedian Mu
      Pages 74-83

    8. Self-Training with Label-Feature-Consistency for Domain Adaptation

      • Yi Xin, Siqi Luo, Pengsheng Jin, Yuntao Du, Chongjun Wang
      Pages 84-99

    9. Meta Pseudo Labels for Anomaly Detection via Partially Observed Anomalies

      • Sinong Zhao, Zhaoyang Yu, Xiaofei Wang, Trent G. Marbach, Gang Wang, Xiaoguang Liu
      Pages 100-109

    10. Learning Enhanced Representations via Contrasting for Multi-view Outlier Detection

      • Xiaocong Chen, Xinye Wang, Yang Wang, Chao Han, Lei Duan
      Pages 110-120

    11. Powering Fine-Tuning: Learning Compatible and Class-Sensitive Representations for Domain Adaption Few-shot Relation Extraction

      • Yijun Liu, Feifei Dai, Xiaoyan Gu, Haihui Fan, Dong Liu, Bo Li et al.
      Pages 121-131

    12. Accelerating Exact K-Means++ Seeding Using Lower Bound Based Framework

      • Haowen Zhang, Jing Li
      Pages 132-141

    13. Modeling Intra-class and Inter-class Constraints for Out-of-Domain Detection

      • Shun Zhang, Jiaqi Bai, Tongliang Li, Zhao Yan, Zhoujun Li
      Pages 142-158

    14. CB-GAN: Generate Sensitive Data with a Convolutional Bidirectional Generative Adversarial Networks

      • Richa Hu, Dan Li, See-Kiong Ng, Zibin Zheng
      Pages 159-174

    15. Rainfall Spatial Interpolation with Graph Neural Networks

      • Jia Li, Yanyan Shen, Lei Chen, Charles Wang Wai Ng
      Pages 175-191

    16. A Knowledge-Driven Memory System for Traffic Flow Prediction

      • Binwu Wang, Yudong Zhang, Pengkun Wang, Xu Wang, Lei Bai, Yang Wang
      Pages 192-207

    17. Weakly-Supervised Multi-action Offline Reinforcement Learning for Intelligent Dosing of Epilepsy in Children

      • Zhuo Li, Yifei Shen, Ruiqing Xu, Yu Yang, Jiannong Cao, Linchun Wu et al.
      Pages 208-223

    18. Fine-Grained Software Vulnerability Detection via Neural Architecture Search

      • Qianjin Du, Xiaohui Kuang, Xiang Li, Gang Zhao
      Pages 224-238

    19. Adversarial Learning-Based Stance Classifier for COVID-19-Related Health Policies

      • Feng Xie, Zhong Zhang, Xuechen Zhao, Haiyang Wang, Jiaying Zou, Lei Tian et al.
      Pages 239-249
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Other volumes

  1. Database Systems for Advanced Applications. DASFAA 2023 International Workshops

  2. Database Systems for Advanced Applications

  3. Database Systems for Advanced Applications

  4. Database Systems for Advanced Applications

  5. Database Systems for Advanced Applications

Keywords

About this book

The four-volume set LNCS 13943, 13944, 13945 and 13946 constitutes the proceedings of the 28th International Conference on Database Systems for Advanced Applications, DASFAA 2023, held in April 2023 in Tianjin, China.

The total of 125 full papers, along with 66 short papers, are presented together in this four-volume set was carefully reviewed and selected from 652 submissions. Additionally, 15 industrial papers, 15 demo papers and 4 PhD consortium papers are included. The conference presents papers on subjects such as model, graph, learning, performance, knowledge, time, recommendation, representation, attention, prediction, and network.

Editors and Affiliations

  • Tianjin University, Tianjin, China

    Xin Wang, Zhiyong Feng

  • University of Torino, Turin, Italy

    Maria Luisa Sapino

  • POSTECH, Pohang, Korea (Republic of)

    Wook-Shin Han

  • University of California Santa Barbara, Santa Barbara, USA

    Amr El Abbadi

  • University of Auckland, Auckland, New Zealand

    Gill Dobbie

  • Beijing University of Posts and Telecommunications, Beijing, China

    Yingxiao Shao

  • The University of Queensland, Brisbane, Australia

    Hongzhi Yin

Bibliographic Information

  • Book Title: Database Systems for Advanced Applications

  • Book Subtitle: 28th International Conference, DASFAA 2023, Tianjin, China, April 17–20, 2023, Proceedings, Part IV

  • Editors: Xin Wang, Maria Luisa Sapino, Wook-Shin Han, Amr El Abbadi, Gill Dobbie, Zhiyong Feng, Yingxiao Shao, … Hongzhi Yin

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-30678-5

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

  • Softcover ISBN: 978-3-031-30677-8Published: 15 April 2023

  • eBook ISBN: 978-3-031-30678-5Published: 13 April 2023

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XXVII, 756

  • Number of Illustrations: 12 b/w illustrations, 229 illustrations in colour

  • Topics: Machine Learning

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