World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
9966
World Ranking
5624
National Ranking
170

Overview

Guandong Xu is affiliated with the University of Technology Sydney in Australia and has contributed extensively to research in Computer Science, with a focus on Artificial Intelligence and Information Systems among other subfields. Their work spans multiple areas such as Computer Vision and Pattern Recognition, Signal Processing, and Sociology and Political Science.

Their recent publications demonstrate a broad engagement with contemporary topics in data and technology. Notable papers include:

  • Future smart cities: requirements, emerging technologies, applications, challenges, and future aspects (2022, Cities)
  • Deep learning for misinformation detection on online social networks: a survey and new perspectives (2020, Social Network Analysis and Mining)
  • Constructing dummy query sequences to protect location privacy and query privacy in location-based services (2020, World Wide Web)
  • Explainable depression detection with multi-aspect features using a hybrid deep learning model on social media (2022, World Wide Web)
  • A Location Privacy-Preserving System Based on Query Range Cover-Up or Location-Based Services (2020, IEEE Transactions on Vehicular Technology)

Guandong Xu's research frequently addresses areas related to privacy preservation, advanced machine learning techniques, and intelligent data processing for social media and urban environments.

Their work includes collaborations with several frequent co-authors, among whom are:

  • Qian Li
  • Xianzhi Wang
  • Hongxu Chen
  • Imran Razzak
  • Qing Li

Publication venues where Guandong Xu has published recurrently reflect their research breadth and include:

  • arXiv (Cornell University)
  • World Wide Web
  • ACM Transactions on Information Systems
  • IEEE Transactions on Knowledge and Data Engineering
  • Neurocomputing

Guandong Xu also has contributions in academic book publishing, including at least one book titled Knowledge Management and Acquisition for Intelligent Systems published by Springer Science+Business Media in 2023.

The scientist's main fields of study encompass:

  • Computer Science

With subfields of study including:

  • Artificial Intelligence
  • Information Systems
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Sociology and Political Science

Core topics of research involve:

  • Recommender Systems and Techniques
  • Advanced Graph Neural Networks
  • Topic Modeling
  • Privacy-Preserving Technologies in Data
  • Sentiment Analysis and Opinion Mining
  • Software Engineering Research
  • Complex Network Analysis Techniques

Best Publications

  • Improving automatic source code summarization via deep reinforcement learning

    Yao Wan;Zhou Zhao;Min Yang;Guandong Xu

  • Sequential recommender system based on hierarchical attention network

    Haochao Ying;Fuzhen Zhuang;Fuzheng Zhang;Yanchi Liu

  • On Deep Learning for Trust-Aware Recommendations in Social Networks

    Shuiguang Deng;Longtao Huang;Guandong Xu;Xindong Wu

  • Personalized recommendation via cross-domain triadic factorization

    Liang Hu;Jian Cao;Guandong Xu;Longbing Cao

  • Algorithms and Techniques

    Guandong Xu;Yanchun Zhang;Lin Li

  • Big data analytics for preventive medicine

    Muhammad Imran Razzak;Muhammad Imran;Guandong Xu

  • Deep learning for misinformation detection on online social networks: a survey and new perspectives

    Rafiqul Islam;Shaowu Liu;Xianzhi Wang;Guandong Xu

  • Social network-based service recommendation with trust enhancement

    Shuiguang Deng;Shuiguang Deng;Longtao Huang;Longtao Huang;Guandong Xu

  • Online IS Education for the 21st Century

    Wu He;Guandong Xu;S. E. Kruck

  • Efficient Brain Tumor Segmentation With Multiscale Two-Pathway-Group Conventional Neural Networks

    Muhammad Imran Razzak;Muhammad Imran;Guandong Xu

  • Web Mining and Social Networking: Techniques and Applications

    Guandong Xu;Yanchun Zhang;Lin Li

  • Constructing dummy query sequences to protect location privacy and query privacy in location-based services

    Zongda Wu;Guiling Li;Shigen Shen;Xinze Lian

  • Refining Parkinson’s neurological disorder identification through deep transfer learning

    Amina Naseer;Monail Rani;Saeeda Naz;Muhammad Imran Razzak

  • Multi-modal attention network learning for semantic source code retrieval

    Yao Wan;Jingdong Shu;Yulei Sui;Guandong Xu

  • Deep Learning for Decision Making and the Optimization of Socially Responsible Investments and Portfolio

    Nhi N.Y. Vo;Xuezhong He;Shaowu Liu;Guandong Xu

  • Fuzzy Cognitive Diagnosis for Modelling Examinee Performance

    Qi Liu;Runze Wu;Enhong Chen;Guandong Xu

  • Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017

    Jana Diesner;Elena Ferrari;Guandong Xu

  • A Boundary-aware Neural Model for Nested Named Entity Recognition

    Changmeng Zheng;Yi Cai;Jingyun Xu;Ho-fung Leung

  • Deep modeling of group preferences for group-based recommendation

    Liang Hu;Jian Cao;Guandong Xu;Longbing Cao

  • Diversifying personalized recommendation with user-session context

    Liang Hu;Longbing Cao;Shoujin Wang;Guandong Xu

Frequent Co-Authors

Yanchun Zhang
Yanchun Zhang Victoria University
Longbing Cao
Longbing Cao University of Technology Sydney
Enhong Chen
Enhong Chen University of Science and Technology of China
Peter Dolog
Peter Dolog Aalborg University
Shuiguang Deng
Shuiguang Deng Zhejiang University
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Xiaofang Zhou
Xiaofang Zhou Hong Kong University of Science and Technology
Masaru Kitsuregawa
Masaru Kitsuregawa University of Tokyo
Xun Yi
Xun Yi RMIT University
Alfredo Cuzzocrea
Alfredo Cuzzocrea University of Calabria

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