High Utility Itemset Mining and Inventory Management: Theory and Use Cases
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Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-6706-3_6
Reference26 articles.
1. Lin, J.C.W., Yang, L., Fournier-Viger, P., Hong, T.P., Voznak, M.: A binary PSO approach to mine high-utility itemsets. Soft. Comput. 21, 5103–5121 (2017). https://doi.org/10.1007/s00500-016-2106-1
2. Lin, J.C.-W., Yang, L., Fournier-Viger, P., Wu, J.M.-T., Hong, T.-P., Wang, L.S.-L., Zhan, J.: Mining high-utility itemsets based on particle swarm optimization. Eng. Appl. Artif. Intell. 55, 320–330 (2016). https://doi.org/10.1016/j.engappai.2016.07.006
3. Chan, R., Yang, Q., Shen, Y.-G.: Mining high utility itemsets. In: Third IEEE International Conference on Data Mining, pp. 19–26. IEEE Computer Society, Melbourne, FL, USA (2003). https://doi.org/10.1109/ICDM.2003.1250893
4. Fournier-Viger, P., Wu, C.-W., Zida, S., Tseng, V.S.: FHM: faster high-utility itemset mining using estimated utility co-occurrence pruning. In: Andreasen, T., Christiansen, H., Cubero, J.C., Raś, Z.W. (eds.) 21st International Symposium on Methodologies for Intelligent Systems, pp. 83–92. Springer, Cham, Roskilde, Denmark (2014). https://doi.org/10.1007/978-3-319-08326-1_9
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