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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:

Anomaly detection in dynamic networks: a survey
Stephen Ranshous, Shitian Shen, Danai Koutra, et al.
Wiley Interdisciplinary Reviews Computational Statistics (2015) Vol. 7, Iss. 3, pp. 223-247
Open Access | Times Cited: 339

Showing 1-25 of 339 citing articles:

A Unifying Review of Deep and Shallow Anomaly Detection
Lukas Ruff, Jacob Kauffmann, Robert A. Vandermeulen, et al.
Proceedings of the IEEE (2021) Vol. 109, Iss. 5, pp. 756-795
Open Access | Times Cited: 690
Continuous-Time Dynamic Network Embeddings
Giang Nguyen, John Boaz Lee, Ryan A. Rossi, et al.
(2018), pp. 969-976
Open Access | Times Cited: 479
Progress in Outlier Detection Techniques: A Survey
Hongzhi Wang, Mohamed Jaward Bah, Mohamed Hammad
IEEE Access (2019) Vol. 7, pp. 107964-108000
Open Access | Times Cited: 426
Community detection in networks: A multidisciplinary review
Muhammad Aqib Javed, Muhammad Shahzad Younis, Siddique Latif, et al.
Journal of Network and Computer Applications (2018) Vol. 108, pp. 87-111
Closed Access | Times Cited: 413
A Comprehensive Survey on Graph Anomaly Detection With Deep Learning
Xiaoxiao Ma, Jia Wu, Shan Xue, et al.
IEEE Transactions on Knowledge and Data Engineering (2021) Vol. 35, Iss. 12, pp. 12012-12038
Open Access | Times Cited: 400
Fraud detection: A systematic literature review of graph-based anomaly detection approaches
Tahereh Pourhabibi, Kok‐Leong Ong, Booi Kam, et al.
Decision Support Systems (2020) Vol. 133, pp. 113303-113303
Open Access | Times Cited: 295
NetWalk
Wenchao Yu, Wei Cheng, Charų C. Aggarwal, et al.
(2018), pp. 2672-2681
Open Access | Times Cited: 289
Information cascades in complex networks
Mahdi Jalili, Matjaž Perc
Journal of Complex Networks (2017)
Closed Access | Times Cited: 235
AddGraph: Anomaly Detection in Dynamic Graph Using Attention-based Temporal GCN
Zheng Li, Zhenpeng Li, Jian Li, et al.
(2019), pp. 4419-4425
Open Access | Times Cited: 180
A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions
Ankit Thakkar, Ritika Lohiya
Artificial Intelligence Review (2021) Vol. 55, Iss. 1, pp. 453-563
Closed Access | Times Cited: 179
Anomaly detection for space information networks: A survey of challenges, techniques, and future directions
Abebe Diro, Shahriar Kaisar, Athanasios V. Vasilakos, et al.
Computers & Security (2024) Vol. 139, pp. 103705-103705
Open Access | Times Cited: 20
Leveraging Machine Learning Techniques for Windows Ransomware Network Traffic Detection
Omar M. Alhawi, James Baldwin, Ali Dehghantanha
Advances in information security (2018), pp. 93-106
Open Access | Times Cited: 153
Big Data Analytics for Intrusion Detection System: Statistical Decision-Making Using Finite Dirichlet Mixture Models
Nour Moustafa, Gideon Creech, Jill Slay
Data analytics (2017), pp. 127-156
Closed Access | Times Cited: 146
D elta C on
Danai Koutra, Neil Shah, Joshua T Vogelstein, et al.
ACM Transactions on Knowledge Discovery from Data (2016) Vol. 10, Iss. 3, pp. 1-43
Open Access | Times Cited: 139
SpotLight
Dhivya Eswaran, Christos Faloutsos, Sudipto Guha, et al.
(2018), pp. 1378-1386
Open Access | Times Cited: 123
A survey of data mining and social network analysis based anomaly detection techniques
Ravneet Kaur, Sarbjeet Singh
Egyptian Informatics Journal (2015) Vol. 17, Iss. 2, pp. 199-216
Open Access | Times Cited: 108
Anomaly Detection using Graph Neural Networks
Anshika Chaudhary, Himangi Mittal, Anuja Arora
2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COM-IT-CON) (2019), pp. 346-350
Closed Access | Times Cited: 80
Urban Anomaly Analytics: Description, Detection, and Prediction
Mingyang Zhang, Tong Li, Yue Yu, et al.
IEEE Transactions on Big Data (2020) Vol. 8, Iss. 3, pp. 809-826
Open Access | Times Cited: 80
Anomaly Detection Methods for Categorical Data
Ayman Taha, Ali S. Hadi
ACM Computing Surveys (2019) Vol. 52, Iss. 2, pp. 1-35
Closed Access | Times Cited: 77
Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs
Lei Cai, Zhengzhang Chen, Chen Luo, et al.
(2021)
Open Access | Times Cited: 77
On the nature and types of anomalies: a review of deviations in data
Ralph Foorthuis
International Journal of Data Science and Analytics (2021) Vol. 12, Iss. 4, pp. 297-331
Open Access | Times Cited: 75
Graph Anomaly Detection With Graph Neural Networks: Current Status and Challenges
Hwan Kim, Byung Suk Lee, Won-Yong Shin, et al.
IEEE Access (2022) Vol. 10, pp. 111820-111829
Open Access | Times Cited: 59
A survey of outlier detection in high dimensional data streams
Imen Souiden, Mohamed Nazih Omri, Zaki Brahmi
Computer Science Review (2022) Vol. 44, pp. 100463-100463
Closed Access | Times Cited: 50
A Survey of Graph-Based Deep Learning for Anomaly Detection in Distributed Systems
Armin Danesh Pazho, Ghazal Alinezhad Noghre, Arnab A Purkayastha, et al.
IEEE Transactions on Knowledge and Data Engineering (2023) Vol. 36, Iss. 1, pp. 1-20
Open Access | Times Cited: 22
Temporal Link Prediction: A Unified Framework, Taxonomy, and Review
Meng Qin, Dit‐Yan Yeung
ACM Computing Surveys (2023) Vol. 56, Iss. 4, pp. 1-40
Open Access | Times Cited: 22
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