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Advanced Data Mining and Applications

19th International Conference, ADMA 2023, Shenyang, China, August 21–23, 2023, Proceedings, Part I

  • Conference proceedings
  • © 2023

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Editors:
  1. Xiaochun Yang

    1. Northeastern University, Shenyang, China

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  2. Heru Suhartanto

    1. The University of Indonesia, Depok, Indonesia

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  3. Guoren Wang

    1. Beijing Institute of Technology, Beijing, China

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  4. Bin Wang

    1. Northeastern University, Shenyang, China

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  5. Jing Jiang

    1. University of Technology Sydney, Sydney, Australia

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  6. Bing Li

    1. Agency for Science, Technology and Research (A*STAR), Singapore, Singapore

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  7. Huaijie Zhu

    1. Sun Yat-sen University, Guangzhou, China

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  8. Ningning Cui

    1. Anhui University, Hefei, China

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14176)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: ADMA 2023.

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Table of contents (54 papers)

  1. Front Matter

    Pages i-xxiv
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  2. Time Series

    1. Front Matter

      Pages 1-1
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    2. An Adaptive Data-Driven Imputation Model for Incomplete Event Series

      • Jiadong Chen, Hengyu Ye, Xiaofeng Gao, Fan Wu, Linghe Kong, Guihai Chen
      Pages 3-18

    3. From Time Series to Multi-modality: Classifying Multivariate Time Series via Both 1D and 2D Representations

      • Chao Yang, Xianzhi Wang, Lina Yao, Guodong Long, Guandong Xu
      Pages 19-33

    4. Exploring the Effectiveness of Positional Embedding on Transformer-Based Architectures for Multivariate Time Series Classification

      • Chao Yang, Yakun Chen, Zihao Li, Xianzhi Wang
      Pages 34-47

    5. Modeling of Repeated Measures for Time-to-event Prediction

      • Jianfei Zhang, Lifei Chen, Shengrui Wang
      Pages 48-63

    6. A Method for Identifying the Timeliness of Manufacturing Data Based on Weighted Timeliness Graph

      • Zehua Liu, Xuefeng Ding, Yuming Jiang, Dasha Hu
      Pages 64-72

    7. STAD: Multivariate Time Series Anomaly Detection Based on Spatio-Temporal Relationship

      • Keyu Chen, Guoping Zhao, Zhenfeng Yao, Zhihong Zhang
      Pages 73-87

  3. Recommendation I

    1. Front Matter

      Pages 89-89
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    2. Refined Node Type Graph Convolutional Network for Recommendation

      • Wei He, Guohao Sun, Jinhu Lu, Xiu Fang, Guanfeng Liu, Jian Yang
      Pages 91-106

    3. Multi-level Noise Filtering and Preference Propagation Enhanced Knowledge Graph Recommendation

      • Ge Zhao, Shuaishuai Zu, Li Li, Zhisheng Yang
      Pages 107-122

    4. Enhancing Knowledge-Aware Recommendation with Contrastive Learning

      • Xinyue Zhang, Hui Gao
      Pages 123-137

    5. Knowledge-Rich Influence Propagation Recommendation Algorithm Based on Graph Attention Networks

      • Yuping Yang, Guifei Jiang, Yuzhi Zhang
      Pages 138-154

    6. A Novel Variational Autoencoder with Multi-position Latent Self-attention and Actor-Critic for Recommendation

      • Jiamei Feng, Mengchi Liu, Song Hong, Shihao Song
      Pages 155-167

    7. Fair Re-Ranking Recommendation Based on Debiased Multi-graph Representations

      • Fangyu Han, Shumei Wang, Jiayu Zhao, Renhui Wu, Xiaobin Rui, Zhixiao Wang
      Pages 168-182

  4. Information Extraction

    1. Front Matter

      Pages 183-183
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    2. FastNER: Speeding up Inferences for Named Entity Recognition Tasks

      • Yuming Zhang, Xiangxiang Gao, Wei Zhu, Xiaoling Wang
      Pages 185-199

    3. CPMFA: A Character Pair-Based Method for Chinese Nested Named Entity Recognition

      • Xiayan Ji, Lina Chen, Fangyao Shen, Hongjie Guo, Hong Gao
      Pages 200-212

    4. STMC-GCN: A Span Tagging Multi-channel Graph Convolutional Network for Aspect Sentiment Triplet Extraction

      • Chao Yang, Jiajie Xing, Xianguo Zhang
      Pages 213-227

    5. Exploring the Design Space of Unsupervised Blocking with Pre-trained Language Models in Entity Resolution

      • Chenchen Sun, Yuyuan Jin, Yang Xu, Derong Shen, Tiezheng Nie, Xite Wang
      Pages 228-244
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Other volumes

  1. Advanced Data Mining and Applications

  2. Advanced Data Mining and Applications

  3. Advanced Data Mining and Applications

  4. Advanced Data Mining and Applications

  5. Advanced Data Mining and Applications

Keywords

About this book

This book constitutes the refereed proceedings of the 19th International Conference on Advanced Data Mining and Applications, ADMA 2023, held in Shenyang, China, during August 21–23, 2023.


The 216 full papers included in this book were carefully reviewed and selected from 503 submissions. They were organized in topical sections as follows: Data mining foundations, Grand challenges of data mining, Parallel and distributed data mining algorithms, Mining on data streams, Graph mining and Spatial data mining.

Editors and Affiliations

  • Northeastern University, Shenyang, China

    Xiaochun Yang, Bin Wang

  • The University of Indonesia, Depok, Indonesia

    Heru Suhartanto

  • Beijing Institute of Technology, Beijing, China

    Guoren Wang

  • University of Technology Sydney, Sydney, Australia

    Jing Jiang

  • Agency for Science, Technology and Research (A*STAR), Singapore, Singapore

    Bing Li

  • Sun Yat-sen University, Guangzhou, China

    Huaijie Zhu

  • Anhui University, Hefei, China

    Ningning Cui

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