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:

Cooperative coevolutionary instance selection for multilabel problems
Nicolás García‐Pedrajas, Gonzalo Cerruela García
Knowledge-Based Systems (2021) Vol. 234, pp. 107569-107569
Open Access | Times Cited: 8

Showing 8 citing articles:

Interval type-2 fuzzy neural networks for multi-label classification
Dayong Tian, Li Fei-Fei, Yiwen Wei
Knowledge-Based Systems (2025), pp. 113014-113014
Open Access

Local-based k values for multi-label k-nearest neighbors rule
J.A. Romero-del-Castillo, Manuel Mendoza-Hurtado, Domingo Ortíz-Boyer, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 116, pp. 105487-105487
Open Access | Times Cited: 21

Evolutionary simultaneous under and oversampling of instances for dealing with class-imbalance datasets in multilabel problems
Nicolás García‐Pedrajas, José M. Cuevas-Muñoz, Aida de Haro-García
Applied Soft Computing (2024) Vol. 159, pp. 111618-111618
Open Access | Times Cited: 2

Partial random under/oversampling for multilabel problems
Nicolás García‐Pedrajas
Knowledge-Based Systems (2024) Vol. 302, pp. 112355-112355
Open Access | Times Cited: 2

Enhancement of DNN-based multilabel classification by grouping labels based on data imbalance and label correlation
Ling Chen, Yuhong Wang, Hao Li
Pattern Recognition (2022) Vol. 132, pp. 108964-108964
Closed Access | Times Cited: 9

A Bayesian network learning method for sparse and unbalanced data with GNN-based multilabel classification application
Ling Chen, Xiangming Jiang, Yuhong Wang
Applied Soft Computing (2024) Vol. 154, pp. 111393-111393
Closed Access | Times Cited: 1

PARIS: Partial instance and training set selection. A new scalable approach to multi-label classification
Nicolás García‐Pedrajas, José M. Cuevas-Muñoz, J.A. Romero-del-Castillo, et al.
Information Fusion (2023) Vol. 95, pp. 120-142
Open Access | Times Cited: 3

Multi-objective Evolutionary Instance Selection for Multi-label Classification
Dingming Liu, Haopu Shang, Wenjing Hong, et al.
Lecture notes in computer science (2022), pp. 548-561
Closed Access

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