journal article·2025Open access

An Active Safe Semi-Supervised Fuzzy Clustering with Pairwise Constraints Based on Cluster Boundary

Duong Tien Dung, Ha Hai Nam, Nguyen Long Giang, Luong Thi Hong Lan

Computers, Materials & Continua· Volume 85· Issue 3

Abstract

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Research context

OpenAlex topics: Face and Expression Recognition · Advanced Clustering Algorithms Research

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References (38)

Show source-provided references
1. Coordinate descent K-means algorithm based on split-merge
2. Relative-density-viewpoint-based weighted kernel fuzzy clustering (RDVWKFC)
3. Bezdek · Pattern recognition with fuzzy objective function algorithms · 2013
4. Fuzzy C-means algorithm automatically determining optimal number of clusters
5. Unsupervised multiview fuzzy c-means clustering algorithm10.3390/electronics12214467 ↗
6. A survey on semi-supervised graph clustering10.1016/j.engappai.2024.108215 ↗
7. Multi-view picture fuzzy clustering: a novel method for partitioning multi-view relational data
8. Semi-supervised fuzzy clustering algorithm based on prior membership degree matrix with expert preference10.1016/j.eswa.2023.121812 ↗
9. Explainable impact of partial supervision in semi-supervised fuzzy clustering10.1109/TFUZZ.2024.3370768 ↗
10. Feature-weight and cluster-weight learning in fuzzy c-means method for semi-supervised clustering10.1016/j.asoc.2024.111712 ↗
11. K-GBS3FCM-KNN graph-based safe semi-supervised fuzzy c-means
12. A novel semi-supervised fuzzy c-means clustering method
13. Pairwise constraints-based semi-supervised fuzzy clustering with multi-manifold regularization10.1016/j.ins.2023.118994 ↗
14. Adaptive semi-supervised fuzzy C-means method with local spatial information and pre-clustering for image segmentation10.1109/ACCESS.2024.3521595 ↗
15. A weighted semi-supervised Possibilistic Fuzzy c-Means algorithm for data stream classification and emerging class detection10.1016/j.knosys.2024.112831 ↗
16. Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study10.1007/s10115-013-0706-y ↗
17. Local homogeneous consistent safe semi-supervised clustering10.1016/j.eswa.2017.12.046 ↗
18. Confidence-weighted safe semi-supervised clustering10.1016/j.engappai.2019.02.007 ↗
19. TS3FCM: trusted safe semi-supervised fuzzy clustering method for data partition with high confidence10.1007/s11042-022-12133-6 ↗
20. Sener O, Savarese S. Active learning for convolutional neural networks: a core-set approach. arXiv:1708.00489. 2017. doi:10.48550/arXiv.1708.00489.
21. A survey on deep active learning: recent advances and new frontiers10.1109/TNNLS.2024.3396463 ↗
22. Active semi-supervised clustering algorithm for multi-density datasets (ASS-DBSCAN)
23. Active learning approach using a modified least confidence sampling strategy for named entity recognition10.1007/s13748-021-00230-w ↗
24. A survey on active learning: state-of-the-art, practical challenges and research directions10.3390/math11040820 ↗
25. Semi-supervised active learning for anomaly detection in aviation
26. Active semi-supervised fuzzy clustering10.1016/j.patcog.2007.10.004 ↗
27. Neighborhood information based semi-supervised fuzzy C-means employing feature-weight and cluster-weight learning10.1016/j.chaos.2024.114670 ↗
28. Interval type-2 fuzzy neural network based on active semi-supervised learning for non-stationary industrial processes10.1109/TASE.2023.3237840 ↗
29. k-means++: the advantages of careful seeding
30. A stratified seed selection algorithm for K-means clustering on big data10.1109/TAI.2024.3524370 ↗
31. Markelle Kelly KN, Rachel L. The UCI machine learning repository [Internet]. [cited 2025 May 15]. Available from: https://archive.ics.uci.edu.
32. Karim MF, Sharma K, Niyar R, Barman NR. Flood area segmentation [Dataset]. Kaggle. 2022; [cited 2025 May 15]. Available from: https://www.kaggle.com/dsv/4732950.
33. On semi-supervised fuzzy c-means clustering
34. Fuzzy semi-supervised clustering with active constraint selection
35. Objective criteria for the evaluation of clustering methods10.1080/01621459.1971.10482356 ↗
36. Application of semi-supervised learning in image classification: research on fusion of labeled and unlabeled data10.1109/ACCESS.2024.3367772 ↗
37. Proof of biased behavior of normalized mutual information10.1038/s41598-024-59073-9 ↗
38. PDBI: a partitioning Davies-Bouldin index for clustering evaluation10.1016/j.neucom.2023.01.043 ↗