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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.

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Showing 14 citing articles:

AutoML: state of the art with a focus on anomaly detection, challenges, and research directions
Maroua Bahri, Flavia Salutari, Andrian Putina, et al.
International Journal of Data Science and Analytics (2022) Vol. 14, Iss. 2, pp. 113-126
Open Access | Times Cited: 79
Meta-features for meta-learning
Adriano Rívolli, Luís P. F. Garcia, Carlos Soares, et al.
Knowledge-Based Systems (2022) Vol. 240, pp. 108101-108101
Open Access | Times Cited: 60
Unsupervised Algorithms to Detect Zero-Day Attacks: Strategy and Application
Tommaso Zoppi, Andrea Ceccarelli, Andrea Bondavalli
IEEE Access (2021) Vol. 9, pp. 90603-90615
Open Access | Times Cited: 45
Real-World Application of Machine Learning and Deep Learning
S. Reema Sree, S.B. Vyshnavi, N. Jayapandian
2019 International Conference on Smart Systems and Inventive Technology (ICSSIT) (2019), pp. 1069-1073
Closed Access | Times Cited: 31
AutoClust: A Framework for Automated Clustering Based on Cluster Validity Indices
Yannis Poulakis, Christos Doulkeridis, Dimosthenis Kyriazis
2021 IEEE International Conference on Data Mining (ICDM) (2020), pp. 1220-1225
Closed Access | Times Cited: 19
Novel Meta-Features for Automated Machine Learning Model Selection in Anomaly Detection
Miloš Kotlar, Marija Punt, Zaharije Radivojević, et al.
IEEE Access (2021) Vol. 9, pp. 89675-89687
Open Access | Times Cited: 15
On the Regressand Noise Problem: Model Robustness and Synergy With Regression-Adapted Noise Filters
Juan José Aguilar Martín, José A. Sáez, Emilio Corchado
IEEE Access (2021) Vol. 9, pp. 145800-145816
Open Access | Times Cited: 10
Towards Understanding Clustering Problems and Algorithms: An Instance Space Analysis
Luiz Henrique dos Santos Fernandes, Ana Carolina Lorena, Kate Smith‐Miles
Algorithms (2021) Vol. 14, Iss. 3, pp. 95-95
Open Access | Times Cited: 9
TPE-AutoClust: A Tree-based Pipline Ensemble Framework for Automated Clustering
Radwa Elshawi, Sherif Sakr
2022 IEEE International Conference on Data Mining Workshops (ICDMW) (2022)
Closed Access | Times Cited: 5
cSmartML: A Meta Learning-Based Framework for Automated Selection and Hyperparameter Tuning for Clustering
Radwa Elshawi, Hudson Lekunze, Sherif Sakr
2021 IEEE International Conference on Big Data (Big Data) (2021), pp. 1119-1126
Closed Access | Times Cited: 6
An English Teaching Resource Recommendation System Based on Network Behavior Analysis
Jing Zhang
Scientific Programming (2021) Vol. 2021, pp. 1-9
Open Access | Times Cited: 5
A Meta-Learning Approach for Software Refactoring
Hanieh Khosravi, Abbas Rasoolzadegan
(2023)
Closed Access | Times Cited: 1
Evaluating Data Characterization Measures for Clustering Problems in Meta-learning
Luiz Henrique dos Santos Fernandes, Marcílio C. P. de Souto, Ana Carolina Lorena
Lecture notes in computer science (2021), pp. 621-632
Closed Access | Times Cited: 1
ML2DAC: Meta-Learning to Democratize AutoML for Clustering Analysis
Dennis Tschechlov, Manuel Fritz, Holger Schwarz, et al.
Proceedings of the ACM on Management of Data (2023) Vol. 1, Iss. 2, pp. 1-26
Closed Access
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