High Average-Utility Pattern Mining Based on Genetic Algorithm with a Novel Pruning Strategy
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-5578-3_1
Reference22 articles.
1. Bhuvaneswari, M., Balaganesh, N., Muneeswaran, K.: H-map-based technique for mining high average utility itemset. IETE J. Res. 47(4), 1–13 (2022)
2. Fournier-Viger, P., Chun-Wei Lin, J., Truong-Chi, T., Nkambou, R.: A survey of high utility itemset mining. In: High-Utility Pattern Mining: Theory, Algorithms and Applications, pp. 1–45. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-04921-8_1
3. Fournier-Viger, P., et al.: The SPMF open-source data mining library version 2. In: Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2016, Riva del Garda, 19–23 September 2016, Proceedings, Part III 16, pp. 36–40. Springer (2016)
4. Han, M., Gao, Z., Li, A., Liu, S., Mu, D.: An overview of high utility itemsets mining methods based on intelligent optimization algorithms. Knowl. Inf. Syst. 64(11), 2945–2984 (2022)
5. Hong, T.P., Lee, C.H., Wang, S.L.: Mining high average-utility itemsets. In: 2009 IEEE International Conference on Systems, Man and Cybernetics, pp. 2526–2530. IEEE (2009)
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