Open Access
| Issue |
EPJ Web Conf.
Volume 341, 2025
2nd International Conference on Advent Trends in Computational Intelligence and Communication Technologies (ICATCICT 2025)
|
|
|---|---|---|
| Article Number | 01003 | |
| Number of page(s) | 9 | |
| DOI | https://doi.org/10.1051/epjconf/202534101003 | |
| Published online | 20 November 2025 | |
- Al-Khoder, A., & Harmouch, H. (2015). Evaluating four of the most popular open source and free data mining tools. International Journal of Academic Scientific Research, 3(10), 13-23. [Google Scholar]
- Yan, X., & Han, J. (2002, December). gspan: Graph-based substructure pattern mining. In 2002 IEEE International Conference on Data Mining, 2002. Proceedings. (pp. 721-724). IEEE. [Google Scholar]
- Salama, A. A., Eisa, M., ELhafeez, S. A., & Lotfy, M. M. (2015). Review of recommender systems algorithms utilized in social networks based e-Learning systems & neutrosophic system. Neutrosophic Sets and Systems, 8, 32-40. [Google Scholar]
- Zhang, J., & Honavar, V. (2004). Learning naive bayes classifiers from attribute value taxonomies and partially specified data. [Google Scholar]
- Agrawal, R., & Srikant, R. (1994, September). Fast algorithms for mining association rules. In Proc. 20th int. conf. very large data bases, VLDB (Vol. 1215, pp. 487-499). [Google Scholar]
- Umarani, V. (2015). A Study on Incremental Association Rule Mining. International Journal of Computer Science and Information Technologies, 6(4), 3961-3964. [Google Scholar]
- Wu, X., Kumar, V., Ross Quinlan, J., Ghosh, J., Yang, Q., Motoda, H. & Steinberg, D. (2008). Top 10 algorithms in data mining. Knowledge and information systems, 14, 1-37. [Google Scholar]
- Phyu, T. N. (2009, March). Survey of classification techniques in data mining. In Proceedings of the international multiconference of engineers and computer scientists (Vol. 1, No. 5, pp. 727-731). Citeseer. [Google Scholar]
- Sahoo, G. (2013). Study of parametric performance evaluation of machine learning and statistical classifiers. International Journal of Information Technology and Computer Science (IJITCS), 5(6), 57. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.