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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 Feature Selection for Big Data Classification: A MapReduce Approach
Daniel Peralta, Sara del Río, Sergio Ramírez‐Gallego, et al.
Mathematical Problems in Engineering (2015) Vol. 2015, pp. 1-11
Open Access | Times Cited: 140

Showing 1-25 of 140 citing articles:

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
Feature Selection for High-Dimensional Data
Verónica Bolón‐Canedo, Noelia Sánchez‐Maroño, Amparo Alonso‐Betanzos
Artificial intelligence: foundations, theory, and algorithms/Artificial intelligence: Foundations, theory, and algorithms (2015)
Closed Access | Times Cited: 245
Feature selection for high-dimensional data
Verónica Bolón‐Canedo, Noelia Sánchez‐Maroño, Amparo Alonso‐Betanzos
Progress in Artificial Intelligence (2016) Vol. 5, Iss. 2, pp. 65-75
Open Access | Times Cited: 231
Transforming big data into smart data: An insight on the use of the k‐nearest neighbors algorithm to obtain quality data
Isaac Triguero, Diego García‐Gil, Jesús Maillo, et al.
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2018) Vol. 9, Iss. 2
Open Access | Times Cited: 188
Heterogeneous Cooperative Co-Evolution Memetic Differential Evolution Algorithm for Big Data Optimization Problems
Nasser R. Sabar, Jemal Abawajy, John Yearwood
IEEE Transactions on Evolutionary Computation (2016) Vol. 21, Iss. 2, pp. 315-327
Closed Access | Times Cited: 118
On the Scalability of Machine-Learning Algorithms for Breast Cancer Prediction in Big Data Context
Sara Alghunaim, Heyam H. Al-Baity
IEEE Access (2019) Vol. 7, pp. 91535-91546
Open Access | Times Cited: 85
Helping university students to choose elective courses by using a hybrid multi-criteria recommendation system with genetic optimization
Aurora Esteban, Amelia Zafra, Cristóbal Romero
Knowledge-Based Systems (2019) Vol. 194, pp. 105385-105385
Open Access | Times Cited: 73
Instance selection of linear complexity for big data
Álvar Arnaiz‐González, José-Francisco Díez-Pastor, Juan J. Rodríguez, et al.
Knowledge-Based Systems (2016) Vol. 107, pp. 83-95
Open Access | Times Cited: 70
Distributed ReliefF-based feature selection in Spark
Raúl-José Palma-Mendoza, Daniel Rodríguez, Luis de‐Marcos
Knowledge and Information Systems (2018) Vol. 57, Iss. 1, pp. 1-20
Closed Access | Times Cited: 69
Deep learning for mining protein data
Qiang Shi, Weiya Chen, Siqi Huang, et al.
Briefings in Bioinformatics (2019) Vol. 22, Iss. 1, pp. 194-218
Closed Access | Times Cited: 67
Centralized vs. distributed feature selection methods based on data complexity measures
Laura Morán‐Fernández, Verónica Bolón‐Canedo, Amparo Alonso‐Betanzos
Knowledge-Based Systems (2016) Vol. 117, pp. 27-45
Closed Access | Times Cited: 66
Fast Genetic Algorithm for feature selection — A qualitative approximation approach
Mohammed Ghaith Altarabichi, Sławomir Nowaczyk, Sepideh Pashami, et al.
Expert Systems with Applications (2022) Vol. 211, pp. 118528-118528
Open Access | Times Cited: 36
Distributed feature selection (DFS) strategy for microarray gene expression data to improve the classification performance
Sai Prasad Potharaju, M. Sreedevi
Clinical Epidemiology and Global Health (2018) Vol. 7, Iss. 2, pp. 171-176
Open Access | Times Cited: 51
Distributed correlation-based feature selection in spark
Raúl-José Palma-Mendoza, Luis de‐Marcos, Daniel Rodríguez, et al.
Information Sciences (2018) Vol. 496, pp. 287-299
Open Access | Times Cited: 47
A parallel metaheuristic approach for ensemble feature selection based on multi-core architectures
Neveen Mohammed Hijazi, Hossam Faris, Ibrahim Aljarah
Expert Systems with Applications (2021) Vol. 182, pp. 115290-115290
Closed Access | Times Cited: 35
Evolutionary Machine Learning With Minions: A Case Study in Feature Selection
Nick Zhang, Abhishek Gupta, Zefeng Chen, et al.
IEEE Transactions on Evolutionary Computation (2021) Vol. 26, Iss. 1, pp. 130-144
Closed Access | Times Cited: 34
When is resampling beneficial for feature selection with imbalanced wide data?
Ismael Ramos‐Pérez, Álvar Arnaiz‐González, Juan J. Rodríguez, et al.
Expert Systems with Applications (2021) Vol. 188, pp. 116015-116015
Open Access | Times Cited: 34
Feature Selection Using Grey Wolf Optimization with Random Differential Grouping
R. S. Latha, B. Saravana Balaji, Nebojša Bačanin, et al.
Computer Systems Science and Engineering (2022) Vol. 43, Iss. 1, pp. 317-332
Open Access | Times Cited: 25
Exploring the influence of waste glass granular replacement on compressive strength in concrete mixtures: a normalization and modeling study
Soran Abdrahman Ahmad, Hemn Unis Ahmed, Serwan Rafiq, et al.
Journal of Building Pathology and Rehabilitation (2024) Vol. 9, Iss. 1
Open Access | Times Cited: 5
Optimising Resource Use Through Low‐Precision Feature Selection: A Performance Analysis of Logarithmic Division and Stochastic Rounding
Samuel Suárez‐Marcote, Laura Morán‐Fernández, Verónica Bolón‐Canedo
Expert Systems (2025) Vol. 42, Iss. 3
Closed Access
Data learning from big data
José L. Torrecilla, Juan Romo
Statistics & Probability Letters (2018) Vol. 136, pp. 15-19
Open Access | Times Cited: 45
MEFASD-BD: Multi-objective evolutionary fuzzy algorithm for subgroup discovery in big data environments - A MapReduce solution
F. Pulgar-Rubio, Antonio J. Rivera, María Dolores Pérez-Godoy, et al.
Knowledge-Based Systems (2016) Vol. 117, pp. 70-78
Closed Access | Times Cited: 38
Scalable Feature Selection via Distributed Diversity Maximization
Sepehr Abbasi Zadeh, Mehrdad Ghadiri, Vahab Mirrokni, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2017) Vol. 31, Iss. 1
Open Access | Times Cited: 38
Adaptive Machine Learning Algorithm and Analytics of Big Genomic Data for Gene Prediction
Oluwafemi A. Sarumi, Carson K. Leung
Intelligent systems reference library (2021), pp. 103-123
Closed Access | Times Cited: 25
Machine and deep learning amalgamation for feature extraction in Industrial Internet-of-Things
P. L. S. Jayalaxmi, Rahul Saha, Gulshan Kumar, et al.
Computers & Electrical Engineering (2021) Vol. 97, pp. 107610-107610
Closed Access | Times Cited: 24
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