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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

The Effects of Random Undersampling with Simulated Class Imbalance for Big Data
Tawfiq Hasanin, Taghi M. Khoshgoftaar
(2018), pp. 70-79
Closed Access | Times Cited: 77

Showing 1-25 of 77 citing articles:

Electricity Theft Detection Using Supervised Learning Techniques on Smart Meter Data
Zahoor Ali Khan, Muhammad Adil, Nadeem Javaid, et al.
Sustainability (2020) Vol. 12, Iss. 19, pp. 8023-8023
Open Access | Times Cited: 96
Global Wildfire Susceptibility Mapping Based on Machine Learning Models
Assaf Shmuel, Eyal Heifetz
Forests (2022) Vol. 13, Iss. 7, pp. 1050-1050
Open Access | Times Cited: 43
Evaluating classifier performance with highly imbalanced Big Data
John Hancock, Taghi M. Khoshgoftaar, Justin Johnson
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 31
Rapid detection of soil heavy metal pollution using hyperspectral data and multiscale spatial network
Haicheng Wang, S. Xiao, R. T. Shen, et al.
Environmental Technology & Innovation (2025) Vol. 37, pp. 104031-104031
Open Access | Times Cited: 1
Sentiment Analysis of Arabic Tweets Regarding Distance Learning in Saudi Arabia during the COVID-19 Pandemic
Malak Aljabri, Sara Mhd. Bachar Chrouf, Norah A. Alzahrani, et al.
Sensors (2021) Vol. 21, Iss. 16, pp. 5431-5431
Open Access | Times Cited: 53
DGM: a data generative model to improve minority class presence in anomaly detection domain
Gcinizwe Dlamini, Muhammad Fahim
Neural Computing and Applications (2021) Vol. 33, Iss. 20, pp. 13635-13646
Closed Access | Times Cited: 46
Comparing performances and effectiveness of machine learning classifiers in detecting financial accounting fraud for Turkish SMEs
Serhan Hamal, Özlem Şenvar
International Journal of Computational Intelligence Systems (2021) Vol. 14, Iss. 1, pp. 769-769
Open Access | Times Cited: 44
Enhancing network intrusion detection: a dual-ensemble approach with CTGAN-balanced data and weak classifiers
Mohammad Reza Abbaszadeh Bavil Soflaei, Arash Salehpour, Karim Samadzamini
The Journal of Supercomputing (2024) Vol. 80, Iss. 11, pp. 16301-16333
Closed Access | Times Cited: 7
A Review on Solution to Class Imbalance Problem: Undersampling Approaches
Debashree Devi, Saroj Biswas, Biswajit Purkayastha
2021 International Conference on Computational Performance Evaluation (ComPE) (2020), pp. 626-631
Closed Access | Times Cited: 48
The effects of class rarity on the evaluation of supervised healthcare fraud detection models
Matthew Herland, Richard A. Bauder, Taghi M. Khoshgoftaar
Journal Of Big Data (2019) Vol. 6, Iss. 1
Open Access | Times Cited: 43
Explainable artificial intelligence for pharmacovigilance: What features are important when predicting adverse outcomes?
Isaac Ronald Ward, Ling Wang, Juan Lü, et al.
Computer Methods and Programs in Biomedicine (2021) Vol. 212, pp. 106415-106415
Open Access | Times Cited: 32
Rapid Visual Screening Feature Importance for Seismic Vulnerability Ranking via Machine Learning and SHAP values
Ioannis Karampinis, Lazaros Iliadis, Athanasios I. Karabinis
(2024)
Open Access | Times Cited: 4
Rebalanced supervised contrastive learning with prototypes for long-tailed visual recognition
Xinyue Chang, Junhai Zhai, Shi-Wen Qiu, et al.
Computer Vision and Image Understanding (2025), pp. 104291-104291
Closed Access
Experimental evaluation of ensemble classifiers for imbalance in Big Data
Mario Juez-Gil, Álvar Arnaiz‐González, Juan J. Rodríguez, et al.
Applied Soft Computing (2021) Vol. 108, pp. 107447-107447
Open Access | Times Cited: 28
Malicious insider threat detection using variation of sampling methods for anomaly detection in cloud environment
S. Asha, D. Shanmugapriya, G. Padmavathi
Computers & Electrical Engineering (2022) Vol. 105, pp. 108519-108519
Closed Access | Times Cited: 16
Developing novel machine-learning-based fire weather indices
Assaf Shmuel, Eyal Heifetz
Machine Learning Science and Technology (2023) Vol. 4, Iss. 1, pp. 015029-015029
Open Access | Times Cited: 10
Machine Learning Classification Workflow and Datasets for Ionospheric VLF Data Exclusion
Filip Arnaut, Aleksandra Kolarski, Vladimir A. Srécković
Data (2024) Vol. 9, Iss. 1, pp. 17-17
Open Access | Times Cited: 3
Temporal compounding increases economic impacts of atmospheric rivers in California
Corinne Bowers, Katherine A. Serafin, Jack W. Baker
Science Advances (2024) Vol. 10, Iss. 3
Open Access | Times Cited: 3
Rapid Visual Screening Feature Importance for Seismic Vulnerability Ranking via Machine Learning and SHAP Values
Ioannis Karampinis, Lazaros Iliadis, Athanasios I. Karabinis
Applied Sciences (2024) Vol. 14, Iss. 6, pp. 2609-2609
Open Access | Times Cited: 3
A Big Data-Driven Hybrid Model for Enhancing Streaming Service Customer Retention Through Churn Prediction Integrated With Explainable AI
Usman Gani Joy, Kazi Ekramul Hoque, Mohammed Nazim Uddin, et al.
IEEE Access (2024) Vol. 12, pp. 69130-69150
Open Access | Times Cited: 3
Investigating Random Undersampling and Feature Selection on Bioinformatics Big Data
Tawfiq Hasanin, Taghi M. Khoshgoftaar, Joffrey L. Leevy, et al.
(2019)
Closed Access | Times Cited: 28
Majority-to-minority resampling for boosting-based classification under imbalanced data
Gaoshan Wang, Jian Wang, Kejing He
Applied Intelligence (2022) Vol. 53, Iss. 4, pp. 4541-4562
Closed Access | Times Cited: 15
Random Forest Classification and Ionospheric Response to Solar Flares: Analysis and Validation
Filip Arnaut, Aleksandra Kolarski, Vladimir A. Srécković
Universe (2023) Vol. 9, Iss. 10, pp. 436-436
Open Access | Times Cited: 8
Determining Resampling Ratios Using BSMOTE and SVM-SMOTE for Identifying Rare Attacks in Imbalanced Cybersecurity Data
Sikha Bagui, Dustin Mink, Subhash C. Bagui, et al.
Computers (2023) Vol. 12, Iss. 10, pp. 204-204
Open Access | Times Cited: 8
Investigating the relationship between time and predictive model maintenance
Joffrey L. Leevy, Taghi M. Khoshgoftaar, Richard A. Bauder, et al.
Journal Of Big Data (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 21
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