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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:

Ordering-based pruning for improving the performance of ensembles of classifiers in the framework of imbalanced datasets
Mikel Galar, Alberto Fernández, Edurne Barrenechea, et al.
Information Sciences (2016) Vol. 354, pp. 178-196
Closed Access | Times Cited: 91

Showing 1-25 of 91 citing articles:

Learning from imbalanced data: open challenges and future directions
Bartosz Krawczyk
Progress in Artificial Intelligence (2016) Vol. 5, Iss. 4, pp. 221-232
Open Access | Times Cited: 2003
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary
Alberto Fernández, Salvador García, Francisco Herrera, et al.
Journal of Artificial Intelligence Research (2018) Vol. 61, pp. 863-905
Open Access | Times Cited: 1533
Improving imbalanced learning through a heuristic oversampling method based on k-means and SMOTE
Georgios Douzas, Fernando Bação, Felix Last
Information Sciences (2018) Vol. 465, pp. 1-20
Open Access | Times Cited: 894
A hybrid ensemble pruning approach based on consensus clustering and multi-objective evolutionary algorithm for sentiment classification
Aytuǧ Onan, Serdar Korukoğlu, Hasan Bulut
Information Processing & Management (2017) Vol. 53, Iss. 4, pp. 814-833
Closed Access | Times Cited: 290
AdaBoost-CNN: An adaptive boosting algorithm for convolutional neural networks to classify multi-class imbalanced datasets using transfer learning
Aboozar Taherkhani, Georgina Cosma, T.M. McGinnity
Neurocomputing (2020) Vol. 404, pp. 351-366
Open Access | Times Cited: 210
Machine learning based mobile malware detection using highly imbalanced network traffic
Zhenxiang Chen, Qiben Yan, Hongbo Han, et al.
Information Sciences (2017) Vol. 433-434, pp. 346-364
Open Access | Times Cited: 172
The improved AdaBoost algorithms for imbalanced data classification
Wenyang Wang, Dongchu Sun
Information Sciences (2021) Vol. 563, pp. 358-374
Closed Access | Times Cited: 142
Biomedical Text Categorization Based on Ensemble Pruning and Optimized Topic Modelling
Aytuǧ Onan
Computational and Mathematical Methods in Medicine (2018) Vol. 2018, pp. 1-22
Open Access | Times Cited: 149
An empirical comparison of techniques for the class imbalance problem in churn prediction
Bing Zhu, Bart Baesens, Seppe K. L. M. vanden Broucke
Information Sciences (2017) Vol. 408, pp. 84-99
Open Access | Times Cited: 147
Review of random forest classification techniques to resolve data imbalance
Anjali S. More, Dipti P. Rana
(2017), pp. 72-78
Closed Access | Times Cited: 132
The study of under- and over-sampling methods’ utility in analysis of highly imbalanced data on osteoporosis
Małgorzata Bach, Aleksandra Werner, Joanna Żywiec, et al.
Information Sciences (2016) Vol. 384, pp. 174-190
Closed Access | Times Cited: 131
Enhanced ensemble structures using wavelet neural networks applied to short-term load forecasting
Gabriel Trierweiler Ribeiro, Viviana Cocco Mariani, Leandro dos Santos Coelho
Engineering Applications of Artificial Intelligence (2019) Vol. 82, pp. 272-281
Closed Access | Times Cited: 130
Instance categorization by support vector machines to adjust weights in AdaBoost for imbalanced data classification
Wonji Lee, Chi‐Hyuck Jun, Jong‐Seok Lee
Information Sciences (2016) Vol. 381, pp. 92-103
Closed Access | Times Cited: 116
A MapReduce approach to diminish imbalance parameters for big deoxyribonucleic acid dataset
Md. Sarwar Kamal, Shamim Ripon, Nilanjan Dey, et al.
Computer Methods and Programs in Biomedicine (2016) Vol. 131, pp. 191-206
Closed Access | Times Cited: 88
Ensemble learning by means of a multi-objective optimization design approach for dealing with imbalanced data sets
Víctor Henrique Alves Ribeiro, Gilberto Reynoso-Meza
Expert Systems with Applications (2020) Vol. 147, pp. 113232-113232
Closed Access | Times Cited: 81
A hybrid data-level ensemble to enable learning from highly imbalanced dataset
Zhi Chen, Jiang Duan, Kang Li, et al.
Information Sciences (2020) Vol. 554, pp. 157-176
Closed Access | Times Cited: 74
FCM-CSMOTE: Fuzzy C-Means Center-SMOTE
Roudani Mohammed, Karim El Moutaouakil
Expert Systems with Applications (2024) Vol. 248, pp. 123406-123406
Closed Access | Times Cited: 11
Optimizing multi-sensor deployment via ensemble pruning for wearable activity recognition
Jingjing Cao, Wenfeng Li, Congcong Ma, et al.
Information Fusion (2017) Vol. 41, pp. 68-79
Closed Access | Times Cited: 69
Online pruning of base classifiers for Dynamic Ensemble Selection
Dayvid V. R. Oliveira, George D. C. Cavalcanti, Robert Sabourin
Pattern Recognition (2017) Vol. 72, pp. 44-58
Closed Access | Times Cited: 64
Optimal Entropy Genetic Fuzzy-C-Means SMOTE (OEGFCM-SMOTE)
Karim El Moutaouakil, M. Roudani, Abdellatif El Ouissari
Knowledge-Based Systems (2022) Vol. 262, pp. 110235-110235
Closed Access | Times Cited: 35
Medical decision support system for extremely imbalanced datasets
Swati Shilaskar, Ashok Ghatol, P. N. Chatur
Information Sciences (2016) Vol. 384, pp. 205-219
Closed Access | Times Cited: 54
Classifier ensemble reduction using a modified firefly algorithm: An empirical evaluation
Zhang Li, Worawut Srisukkham, Siew Chin Neoh, et al.
Expert Systems with Applications (2017) Vol. 93, pp. 395-422
Open Access | Times Cited: 51
Prediction of igneous lithology and lithofacies based on ensemble learning with data optimization
Ruiyi Han, Zhuwen Wang, Zhitao Zhang, et al.
Geophysics (2024) Vol. 89, Iss. 2, pp. JM1-JM11
Closed Access | Times Cited: 4
Evolutionary optimization of the area under precision-recall curve for classifying imbalanced multi-class data
Marwa Chabbouh, Marwa Chabbouh, Efrén Mezura‐Montes, et al.
Journal of Heuristics (2025) Vol. 31, Iss. 1
Closed Access
Multifeature, Sparse-Based Approach for Defects Detection and Classification in Semiconductor Units
Bashar Haddad, Sen Yang, Lina J. Karam, et al.
IEEE Transactions on Automation Science and Engineering (2016) Vol. 15, Iss. 1, pp. 145-159
Closed Access | Times Cited: 43
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