World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
3851
World Ranking
12785
National Ranking
8

Overview

Bay Vo is affiliated with Ho Chi Minh City University of Technology in Vietnam. Their research contributions are primarily within the field of Computer Science, focusing on several specialized subfields and topics.

The main fields of study in which Bay Vo has published include:

  • Computer Science (123 publications)

The subfields of study frequently addressed in their work include:

  • Artificial Intelligence (38 publications)
  • Information Systems (38 publications)
  • Computational Theory and Mathematics (25 publications)
  • Signal Processing (13 publications)
  • Computer Networks and Communications (7 publications)

Bay Vo's research topics cover areas such as:

  • Data Mining Algorithms and Applications (64 publications)
  • Rough Sets and Fuzzy Logic (44 publications)
  • Data Management and Algorithms (22 publications)
  • Imbalanced Data Classification Techniques (20 publications)
  • Advanced Database Systems and Queries (12 publications)
  • Data Stream Mining Techniques (8 publications)
  • Topic Modeling (8 publications)

Their recent published papers include:

  • "A multiple multilayer perceptron neural network with an adaptive learning algorithm for thyroid disease diagnosis in the internet of medical things," 2020, The Journal of Supercomputing
  • "Improving security using SVM-based anomaly detection: issues and challenges," 2020, Soft Computing
  • "Approximate high utility itemset mining in noisy environments," 2020, Knowledge-Based Systems
  • "RHUPS," 2021, ACM Transactions on Intelligent Systems and Technology
  • "EHMIN: Efficient approach of list based high-utility pattern mining with negative unit profits," 2022, Expert Systems with Applications

Bay Vo collaborates frequently with several coauthors, including:

  • Loan T. T. Nguyen (24 coauthored papers)
  • Unil Yun (17 coauthored papers)
  • Trinh D. D. Nguyen (8 coauthored papers)
  • Jerry Chun-Wei Lin (7 coauthored papers)
  • Heonho Kim (6 coauthored papers)

Their work often appears in recurring publication venues, such as:

  • Information Sciences (8 publications)
  • Applied Intelligence (6 publications)
  • IEEE Access (5 publications)
  • Expert Systems with Applications (2 publications)
  • Knowledge-Based Systems (2 publications)

Best Publications

  • A survey of itemset mining

    Philippe Fournier‐Viger;Jerry Chun‐Wei Lin;Bay Vo;Bay Vo;Tin Truong Chi

  • Improving electric energy consumption prediction using CNN and Bi-LSTM

    Tuong Le;Minh Thanh Vo;Bay Vo;Eenjun Hwang

  • A graph-based CNN-LSTM stock price prediction algorithm with leading indicators

    Jimmy Ming-Tai Wu;Zhongcui Li;Norbert Herencsar;Bay Vo

  • A new method for mining Frequent Weighted Itemsets based on WIT-trees

    Bay Vo;Frans Coenen;Bac Le

  • DBV-Miner: A Dynamic Bit-Vector approach for fast mining frequent closed itemsets

    Bay Vo;Tzung-Pei Hong;Bac Le

  • Mining frequent itemsets using the N-list and subsume concepts

    Bay Vo;Tuong Le;Frans Coenen;Tzung-Pei Hong

  • A multiple multilayer perceptron neural network with an adaptive learning algorithm for thyroid disease diagnosis in the internet of medical things

    Mehdi Hosseinzadeh;Omed Hassan Ahmed;Marwan Yassin Ghafour;Fatemeh Safara

  • Improving security using SVM-based anomaly detection: issues and challenges

    Mehdi Hosseinzadeh;Mehdi Hosseinzadeh;Amir Masoud Rahmani;Bay Vo;Moazam Bidaki

  • Multi-Objective Task and Workflow Scheduling Approaches in Cloud Computing: a Comprehensive Review

    Mehdi Hosseinzadeh;Mehdi Hosseinzadeh;Marwan Yassin Ghafour;Hawkar Kamaran Hama;Bay Vo

  • Mining high-utility itemsets in dynamic profit databases

    Loan T.T. Nguyen;Phuc Nguyen;Trinh D.D. Nguyen;Bay Vo

  • A Hybrid Approach Using Oversampling Technique and Cost-Sensitive Learning for Bankruptcy Prediction

    Tuong Le;Minh Thanh Vo;Bay Vo;Mi Young Lee

  • A lattice-based approach for mining most generalization association rules

    Bay Vo;Tzung-Pei Hong;Bac Le

  • High-Utility Pattern Mining

    Unknown

  • MEI: An efficient algorithm for mining erasable itemsets

    Tuong Le;Bay Vo

  • Classification based on association rules: A lattice-based approach

    Loan T. T. Nguyen;Bay Vo;Tzung-Pei Hong;Hoang Chi Thanh

  • A New Method for Mining High Average Utility Itemsets

    Tien Lu;Bay Vo;Hien T. Nguyen;Tzung-Pei Hong

  • A lattice-based approach for mining high utility association rules

    Thang Mai;Bay Vo;Loan T.T. Nguyen

  • A fast and accurate approach for bankruptcy forecasting using squared logistics loss with GPU-based extreme gradient boosting

    Tuong Le;Bay Vo;Hamido Fujita;Ngoc Thanh Nguyen

  • CAR-Miner

    Loan T.T. Nguyen;Bay Vo;Tzung-Pei Hong;Hoang Chi Thanh

  • An efficient and effective algorithm for mining top-rank-k frequent patterns

    Quyen Huynh-Thi-Le;Tuong Le;Bay Vo;Bac Le

  • New similarity measures for single-valued neutrosophic sets with applications in pattern recognition and medical diagnosis problems

    Jia Syuen Chai;Ganeshsree Selvachandran;Florentin Smarandache;Vassilis C. Gerogiannis

  • An efficient method for mining high utility closed itemsets

    Loan T.T. Nguyen;Vinh V. Vu;Mi T.H. Lam;Thuy T.M. Duong

  • A novel approach for mining maximal frequent patterns

    Bay Vo;Sang Pham;Tuong Le;Zhi-Hong Deng

  • Efficient transaction deleting approach of pre-large based high utility pattern mining in dynamic databases

    Unil Yun;Hyoju Nam;Jongseong Kim;Heonho Kim

Frequent Co-Authors

Tzung-Pei Hong
Tzung-Pei Hong National University of Kaohsiung
Witold Pedrycz
Witold Pedrycz University of Alberta
Unil Yun
Unil Yun Sejong University
Vaclav Snasel
Vaclav Snasel VSB – Technical University of Ostrava
Philippe Fournier-Viger
Philippe Fournier-Viger Shenzhen University
Mehdi Hosseinzadeh
Mehdi Hosseinzadeh Washington State University
Sung Wook Baik
Sung Wook Baik Sejong University
Hamido Fujita
Hamido Fujita University of Technology Malaysia
Frans Coenen
Frans Coenen University of Liverpool
Vincent S. Tseng
Vincent S. Tseng National Yang Ming Chiao Tung University

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