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Database Systems for Advanced Applications

26th International Conference, DASFAA 2021, Taipei, Taiwan, April 11–14, 2021, Proceedings, Part III

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. Christian S. Jensen

    1. Aalborg University, Aalborg, Denmark

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  2. Ee-Peng Lim

    1. Singapore Management University, Singapore, Singapore

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  3. De-Nian Yang

    1. Academia Sinica, Taipei, Taiwan

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  4. Wang-Chien Lee

    1. The Pennsylvania State University, University Park, USA

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  5. Vincent S. Tseng

    1. National Chiao Tung University, Hsinchu, Taiwan

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  6. Vana Kalogeraki

    1. Athens University of Economics and Business, Athens, Greece

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  7. Jen-Wei Huang

    1. National Cheng Kung University, Tainan City, Taiwan

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  8. Chih-Ya Shen

    1. National Tsing Hua University, Hsinchu, Taiwan

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12683)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: DASFAA 2021.

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Table of contents (54 papers)

  1. Front Matter

    Pages i-xxiv
    Download chapter PDF

  2. Recommendation

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Gated Sequential Recommendation System with Social and Textual Information Under Dynamic Contexts

      • Haoyu Geng, Shuodian Yu, Xiaofeng Gao
      Pages 3-19

    3. SRecGAN: Pairwise Adversarial Training for Sequential Recommendation

      • Guangben Lu, Ziheng Zhao, Xiaofeng Gao, Guihai Chen
      Pages 20-35

    4. SSRGAN: A Generative Adversarial Network for Streaming Sequential Recommendation

      • Yao Lv, Jiajie Xu, Rui Zhou, Junhua Fang, Chengfei Liu
      Pages 36-52

    5. Topological Interpretable Multi-scale Sequential Recommendation

      • Tao Yuan, Shuzi Niu, Huiyuan Li
      Pages 53-68

    6. SANS: Setwise Attentional Neural Similarity Method for Few-Shot Recommendation

      • Zhenghao Zhang, Tun Lu, Dongsheng Li, Peng Zhang, Hansu Gu, Ning Gu
      Pages 69-84

    7. Semi-supervised Factorization Machines for Review-Aware Recommendation

      • Junheng Huang, Fangyuan Luo, Jun Wu
      Pages 85-99

    8. DCAN: Deep Co-Attention Network by Modeling User Preference and News Lifecycle for News Recommendation

      • Lingkang Meng, Chongyang Shi, Shufeng Hao, Xiangrui Su
      Pages 100-114

    9. Considering Interaction Sequence of Historical Items for Conversational Recommender System

      • Xintao Tian, Yongjing Hao, Pengpeng Zhao, Deqing Wang, Yanchi Liu, Victor S. Sheng
      Pages 115-131

    10. Knowledge-Aware Hypergraph Neural Network for Recommender Systems

      • Binghao Liu, Pengpeng Zhao, Fuzhen Zhuang, Xuefeng Xian, Yanchi Liu, Victor S. Sheng
      Pages 132-147

    11. Personalized Dynamic Knowledge-Aware Recommendation with Hybrid Explanations

      • Hao Sun, Zijian Wu, Yue Cui, Liwei Deng, Yan Zhao, Kai Zheng
      Pages 148-164

    12. Graph Attention Collaborative Similarity Embedding for Recommender System

      • Jinbo Song, Chao Chang, Fei Sun, Zhenyang Chen, Guoyong Hu, Peng Jiang
      Pages 165-178

    13. Learning Disentangled User Representation Based on Controllable VAE for Recommendation

      • Yunyi Li, Pengpeng Zhao, Deqing Wang, Xuefeng Xian, Yanchi Liu, Victor S. Sheng
      Pages 179-194

    14. DFCN: An Effective Feature Interactions Learning Model for Recommender Systems

      • Wei Yang, Tianyu Hu
      Pages 195-210

    15. Tell Me Where to Go Next: Improving POI Recommendation via Conversation

      • Changheng Li, Yongjing Hao, Pengpeng Zhao, Fuzhen Zhuang, Yanchi Liu, Victor S. Sheng
      Pages 211-227

    16. MISS: A Multi-user Identification Network for Shared-Account Session-Aware Recommendation

      • Xinyu Wen, Zhaohui Peng, Shanshan Huang, Senzhang Wang, Philip S. Yu
      Pages 228-243

    17. VizGRank: A Context-Aware Visualization Recommendation Method Based on Inherent Relations Between Visualizations

      • Qianfeng Gao, Zhenying He, Yinan Jing, Kai Zhang, X. Sean Wang
      Pages 244-261

    18. Deep User Representation Construction Model for Collaborative Filtering

      • Daomin Ji, Zhenglong Xiang, Yuanxiang Li
      Pages 262-278

    19. DiCGAN: A Dilated Convolutional Generative Adversarial Network for Recommender Systems

      • Zhiqiang Guo, Chaoyang Wang, Jianjun Li, Guohui Li, Peng Pan
      Pages 279-296
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Other volumes

  1. Database Systems for Advanced Applications. DASFAA 2021 International Workshops

  2. Database Systems for Advanced Applications

  3. Database Systems for Advanced Applications

  4. Database Systems for Advanced Applications

Keywords

About this book

The three-volume set LNCS 12681-12683 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021.

The total of 156 papers presented in this three-volume set was carefully reviewed and selected from 490 submissions.

The topic areas for the selected papers include information retrieval, search and recommendation techniques; RDF, knowledge graphs, semantic web, and knowledge management; and spatial, temporal, sequence, and streaming data management, while the dominant keywords are network, recommendation, graph, learning, and model. These topic areas and keywords shed the light on the direction where the research in DASFAA is moving towards.

Due to the Corona pandemic this event was held virtually.

Editors and Affiliations

  • Aalborg University, Aalborg, Denmark

    Christian S. Jensen

  • Singapore Management University, Singapore, Singapore

    Ee-Peng Lim

  • Academia Sinica, Taipei, Taiwan

    De-Nian Yang

  • The Pennsylvania State University, University Park, USA

    Wang-Chien Lee

  • National Chiao Tung University, Hsinchu, Taiwan

    Vincent S. Tseng

  • Athens University of Economics and Business, Athens, Greece

    Vana Kalogeraki

  • National Cheng Kung University, Tainan City, Taiwan

    Jen-Wei Huang

  • National Tsing Hua University, Hsinchu, Taiwan

    Chih-Ya Shen

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