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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:

Evolutionary undersampling for imbalanced big data classification
Isaac Triguero, Mikel Galar, Sarah Vluymans, et al.
2022 IEEE Congress on Evolutionary Computation (CEC) (2015)
Open Access | Times Cited: 53

Showing 1-25 of 53 citing articles:

A survey on addressing high-class imbalance in big data
Joffrey L. Leevy, Taghi M. Khoshgoftaar, Richard A. Bauder, et al.
Journal Of Big Data (2018) Vol. 5, Iss. 1
Open Access | Times Cited: 623
Big data preprocessing: methods and prospects
Salvador García, Sergio Ramírez‐Gallego, Julián Luengo, et al.
Big Data Analytics (2016) Vol. 1, Iss. 1
Open Access | Times Cited: 561
An insight into imbalanced Big Data classification: outcomes and challenges
Alberto Fernández, Sara del Río, Nitesh V. Chawla, et al.
Complex & Intelligent Systems (2017) Vol. 3, Iss. 2, pp. 105-120
Open Access | Times Cited: 208
Multiset Feature Learning for Highly Imbalanced Data Classification
Xiao‐Yuan Jing, Xinyu Zhang, Xiaoke Zhu, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2019) Vol. 43, Iss. 1, pp. 139-156
Closed Access | Times Cited: 112
The balancing trick: Optimized sampling of imbalanced datasets—A brief survey of the recent State of the Art
Seba Susan, Amitesh Kumar
Engineering Reports (2020) Vol. 3, Iss. 4
Open Access | Times Cited: 78
Automatic design of machine learning via evolutionary computation: A survey
Nan Li, Lianbo Ma, Tiejun Xing, et al.
Applied Soft Computing (2023) Vol. 143, pp. 110412-110412
Closed Access | Times Cited: 27
Improved Overlap-based Undersampling for Imbalanced Dataset Classification with Application to Epilepsy and Parkinson’s Disease
Pattaramon Vuttipittayamongkol, Eyad Elyan
International Journal of Neural Systems (2020) Vol. 30, Iss. 08, pp. 2050043-2050043
Open Access | Times Cited: 66
A Classification Method Based on Feature Selection for Imbalanced Data
Yi Liu, Yanzhen Wang, Xiaoguang Ren, et al.
IEEE Access (2019) Vol. 7, pp. 81794-81807
Open Access | Times Cited: 56
A Survey on Unbalanced Classification: How Can Evolutionary Computation Help?
Wenbin Pei, Bing Xue, Mengjie Zhang, et al.
IEEE Transactions on Evolutionary Computation (2023) Vol. 28, Iss. 2, pp. 353-373
Closed Access | Times Cited: 19
A literature survey on various aspect of class imbalance problem in data mining
Shivani Goswami, Anil Kumar Singh
Multimedia Tools and Applications (2024) Vol. 83, Iss. 27, pp. 70025-70050
Closed Access | Times Cited: 5
Evolutionary undersampling for extremely imbalanced big data classification under apache spark
Isaac Triguero, Mikel Galar, Dolores Merino, et al.
2022 IEEE Congress on Evolutionary Computation (CEC) (2016), pp. 640-647
Open Access | Times Cited: 60
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
Bio-inspired computation for big data fusion, storage, processing, learning and visualization: state of the art and future directions
Ana I. Torre-Bastida, Josu Díaz-de-Arcaya, Eneko Osaba, et al.
Neural Computing and Applications (2021)
Open Access | Times Cited: 28
A distributed approach to multi-objective evolutionary generation of fuzzy rule-based classifiers from big data
Andrea Ferranti, Francesco Marcelloni, Armando Segatori, et al.
Information Sciences (2017) Vol. 415-416, pp. 319-340
Open Access | Times Cited: 36
EUSC: A clustering-based surrogate model to accelerate evolutionary undersampling in imbalanced classification
Hoang Lam Le, Dario Landa-Silva, Mikel Galar, et al.
Applied Soft Computing (2020) Vol. 101, pp. 107033-107033
Open Access | Times Cited: 27
A Comparative Analysis on Recent Methods for Addressing Imbalance Classification
Zahid Ahmed, Sufal Das
SN Computer Science (2023) Vol. 5, Iss. 1
Closed Access | Times Cited: 8
EvoPreprocess—Data Preprocessing Framework with Nature-Inspired Optimization Algorithms
Sašo Karakatič
Mathematics (2020) Vol. 8, Iss. 6, pp. 900-900
Open Access | Times Cited: 21
A first attempt on global evolutionary undersampling for imbalanced big data
Isaac Triguero, Mikel Galar, Humberto Bustince, et al.
2022 IEEE Congress on Evolutionary Computation (CEC) (2017)
Open Access | Times Cited: 23
A scalable and distributed dendritic cell algorithm for big data classification
Zaineb Chelly Dagdia
Swarm and Evolutionary Computation (2018) Vol. 50, pp. 100432-100432
Open Access | Times Cited: 22
Analysis of Bayesian optimization algorithms for big data classification based on Map Reduce framework
Chitrakant Banchhor, N. Srinivasu
Journal Of Big Data (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 17
Feature Selection, Online Feature Selection Techniques for Big Data Classification: - A Review
S. Gayathri Devi, M. Sabrigiriraj
2018 International Conference on Current Trends towards Converging Technologies (ICCTCT) (2018), pp. 1-9
Closed Access | Times Cited: 20
A Survey on Big Data Pre-processing
Zhibin Guan, Tongkai Ji, Qian Xu, et al.
(2017), pp. 241-247
Closed Access | Times Cited: 20
SetConv: A New Approach for Learning from Imbalanced Data
Yang Gao, Yifan Li, Yu Lin, et al.
(2020), pp. 1284-1294
Open Access | Times Cited: 13
Proposed big data architecture for facial recognition using machine learning
Suriya Priya R. Asaithambi, Sitalakshmi Venkatraman, Ramanathan Venkatraman
AIMS Electronics and Electrical Engineering (2021) Vol. 5, Iss. 1, pp. 68-92
Open Access | Times Cited: 11
Improving nearest neighbor classification using Ensembles of Evolutionary Generated Prototype Subsets
Nele Verbiest, Sarah Vluymans, Chris Cornelis, et al.
Applied Soft Computing (2016) Vol. 44, pp. 75-88
Closed Access | Times Cited: 11
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