World's Best Scientists 2026 revealed!

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Computer Science

D-Index
63
Citations
17433
World Ranking
2737
National Ranking
373

Overview

Ada Wai-Chee Fu is affiliated with the Chinese University of Hong Kong in China. Their research primarily spans the field of Computer Science, with a particular focus on Artificial Intelligence and Signal Processing alongside other subfields.

Their scholarly work covers several topics including:

  • Data Management and Algorithms
  • Geographic Information Systems Studies
  • Mobile Ad Hoc Networks
  • Algorithms and Data Compression
  • Advanced Image and Video Retrieval Techniques
  • Advanced Graph Neural Networks
  • Topic Modeling

Ada Wai-Chee Fu's publication record comprises various recent papers, notably:

  • "Optimal location query based on k nearest neighbours," 2021, Frontiers of Computer Science
  • "Towards Secure and Efficient Equality Conjunction Search Over Outsourced Databases," 2020, IEEE Transactions on Cloud Computing
  • "k-Pleased Querying," 2021, IEEE Transactions on Knowledge and Data Engineering
  • "k-Pleased Querying (Extended Abstract)," 2022, 2022 IEEE 38th International Conference on Data Engineering (ICDE)

Their work has appeared in well-regarded publication venues, including:

  • Frontiers of Computer Science
  • IEEE Transactions on Knowledge and Data Engineering
  • IEEE Transactions on Cloud Computing
  • 2022 IEEE 38th International Conference on Data Engineering (ICDE)

Ada Wai-Chee Fu often collaborates with a consistent group of coauthors. Frequent coauthors include:

  • Zitong Chen
  • Cheng Long
  • Raymond Chi-Wing Wong
  • Yang Wu
  • Yubao Liu

Their research contributions engage with a variety of computational challenges, ranging from efficient query processing and database security to advanced querying techniques and geographic information systems. This multidisciplinary approach encompasses both theoretical algorithms and practical applications within computer science domains.

Best Publications

  • Efficient time series matching by wavelets

    Kin-Pong Chan;Ada Wai-Chee Fu

  • HOT SAX: efficiently finding the most unusual time series subsequence

    E. Keogh;J. Lin;A. Fu

  • Entropy-based subspace clustering for mining numerical data

    Chun-Hung Cheng;Ada Waichee Fu;Yi Zhang

  • A fast distributed algorithm for mining association rules

    D.W. Cheung;Jiawei Han;V.T. Ng;A.W. Fu

  • Enhancing Effectiveness of Outlier Detections for Low Density Patterns

    Jian Tang;Zhixiang Chen;Ada Wai-Chee Fu;David Wai-Lok Cheung

  • Mining association rules with weighted items

    C.H. Cai;A.W.C. Fu;C.H. Cheng;W.W. Kwong

  • Utility-based anonymization using local recoding

    Jian Xu;Wei Wang;Jian Pei;Xiaoyuan Wang

  • (α, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing

    Raymond Chi-Wing Wong;Jiuyong Li;Ada Wai-Chee Fu;Ke Wang

  • Efficient mining of association rules in distributed databases

    D.W. Cheung;V.T. Ng;A.W. Fu;Yongjian Fu

  • K-isomorphism: privacy preserving network publication against structural attacks

    James Cheng;Ada Wai-chee Fu;Jia Liu

  • Minimality attack in privacy preserving data publishing

    Raymond Chi-Wing Wong;Ada Wai-Chee Fu;Ke Wang;Jian Pei

  • Haar wavelets for efficient similarity search of time-series: with and without time warping

    F.K.-P. Chan;A.W.-C. Fu;C. Yu

  • Enhanced nearest neighbour search on the R-tree

    King Lum Cheung;Ada Wai-Chee Fu

  • Discovering Temporal Patterns for Interval-Based Events

    Po-shan Kam;Ada Wai-Chee Fu

  • Anonymizing transaction databases for publication

    Yabo Xu;Ke Wang;Ada Wai-Chee Fu;Philip S. Yu

  • Introduction to Privacy-Preserving Data Publishing: Concepts and Techniques

    Benjamin C.M. Fung;Ke Wang;Ada Wai-Chee Fu;Philip S. Yu

  • Scaling and time warping in time series querying

    Ada Wai-chee Fu;Eamonn Keogh;Leo Yung Hang Lau;Chotirat Ann Ratanamahatana

  • Efficient anomaly monitoring over moving object trajectory streams

    Yingyi Bu;Lei Chen;Ada Wai-Chee Fu;Dawei Liu

  • Query Expansion

    Unknown

  • Approximations to magic: finding unusual medical time series

    J. Lin;E. Keogh;Ada Fu;H. Van Herle

  • Mining frequent itemsets without support threshold: with and without item constraints

    Yin-Ling Cheung;Ada Wai-Chee Fu

Frequent Co-Authors

Raymond Chi-Wing Wong
Raymond Chi-Wing Wong Hong Kong University of Science and Technology
Ke Wang
Ke Wang Simon Fraser University
Jian Pei
Jian Pei Duke University
James Cheng
James Cheng Chinese University of Hong Kong
David W. Cheung
David W. Cheung University of Hong Kong
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Lei Chen
Lei Chen Hong Kong University of Science and Technology
Jiuyong Li
Jiuyong Li University of South Australia
Eamonn Keogh
Eamonn Keogh University of California, Riverside
Jeffrey Xu Yu
Jeffrey Xu Yu Chinese University of Hong Kong

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