Data Quality Evaluation Method Based on Density Clustering Algorithm and Its Application
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9538-7_8
Reference12 articles.
1. Purushothaman, R., Selvakumar, S., Rajagopalan, S.P.: Hybrid grasshopper and chameleon swarm optimization algorithm for text feature selection with density peaks clustering. Int. J. Comput. Intell. Appl. 21(3), 2250018:1–2250018:18 (2022)
2. Phamtoan, D., Vovan, T.: Automatic fuzzy clustering for probability density functions using the genetic algorithm. Neural Comput. Appl. 34(17), 14609–14625 (2022)
3. Khader, M., Al-Naymat, G.: Density-based algorithms for Big Data clustering using MapReduce framework: a comprehensive study. ACM Comput. Surv. 53(5), 93:1–93:38 (2021)
4. Jaya Lakshmi, B., Madhuri, K.B., Shashi, M.: Efficient hybrid algorithms for density based subspace clustering to deal with density divergence for improved quality and conciseness. Evol. Syst. 12(2), 489–501 (2021)
5. Bali, B., Singh, B.M.: Unification of firefly algorithm with density-based spatial clustering for segmentation of medical images. Int. J. Comput. Appl. Technol. 65(4), 316–324 (2021)
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