A semi-supervised framework for concept-based hierarchical document clustering
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Software
Link
https://link.springer.com/content/pdf/10.1007/s11280-023-01209-4.pdf
Reference60 articles.
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2. Janani, R., Vijayarani, S.: Text document clustering using Spectral Clustering algorithm with Particle Swarm Optimization. Expert Syst. Appl. 134, 192–200 (2019). https://doi.org/10.1016/J.ESWA.2019.05.030
3. Zhang, W., Yoshida, T., Tang, X., Wang, Q.: Text clustering using frequent itemsets. Knowledge-Based Syst. 23, 379–388 (2010). https://doi.org/10.1016/j.knosys.2010.01.011
4. Xiao, Y., Liu, B., Yin, J., Hao, Z.: A multiple-instance stream learning framework for adaptive document categorization. Knowledge-Based Syst. 120, 198–210 (2017). https://doi.org/10.1016/j.knosys.2017.01.001
5. Misztal-Radecka, J., Indurkhya, B.: Bias-Aware Hierarchical Clustering for detecting the discriminated groups of users in recommendation systems. Inf. Process. Manag. 58, 102519 (2021). https://doi.org/10.1016/J.IPM.2021.102519
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