EXPLOIT MINING HIGH UTILITY ITEMSETS WITH NEGATIVE UNIT PROFITS FROM VERTICALLY DISTRIBUTED DATABASES
DOI:
https://doi.org/10.37569/DalatUniversity.10.3.666(2020)Keywords:
Data mining, Database, High utility itemset, Negative unit profits, Vertically distributed databases.Abstract
High Utility Itemset (HUI) mining is an important problem in the data mining literature that considers the utilities for businesses of items (such as profits and margins) that are discovered from transactional databases. There are many algorithms for mining high utility itemsets (HUIs) by pruning candidates based on estimated and transaction-weighted utilization values. These algorithms aim to reduce the search space. In this paper, we propose a method for mining HUIs with negative unit profits from vertically distributed databases. This method does not integrate databases from the relevant local databases to form a centralized database. Experiments show that the run-time of this method is more efficient than that of the centralized database.
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References
Agrawal, R., & Shafer, J. C. (1996). Parallel mining of association rules. IEEE Transactions on knowledge and Data Engineering, 8(6), 962-969. http://doi.org/10.1109/69.553164.
Erwin, A., Gopalan, R. P., & Achuthan, N. R. (2007a). CTU-Mine: An efficient high utility itemset mining algorithm using the pattern growth approach. Paper presented at The 7th IEEE International Conference on Computer and Information Technology (CIT 2007), Fukushima, Japan. http://doi.org/10.1109/CIT.2007.120.
Erwin, A., Gopalan, R. P., & Achuthan, N. R. (2007b). A bottom-up projection based algorithm for mining high utility itemsets. In K. L. Ong, W. Li, & J. Gao (Eds.), Proceedings of the 2nd international workshop on Integrating artificial intelligence and data mining - Volume 84 (pp. 3-11). Australian Computer Society Inc, Australia.
Gopalan, R. P., & Sucahyo, Y. G. (2004). High performance frequent patterns extraction using compressed FP-tree. Paper presented at The SIAM International Workshop on High Performance and Distributed Mining (HPDM), Orlando, USA.
Le, B., Nguyen, H., Cao, T. A., & Vo, B. (2009). A novel algorithm for mining high utility itemsets. Paper presented at The 2009 First Asian Conference on Intelligent Information and Database Systems, Donghoi, Quangbinh, Vietnam. http://doi.org/ 10.1109/ACIIDS.2009.55
Lin, J. C. W., Fournier-Viger, P., & Gan, W. (2016). FHN: An efficient algorithm for mining high-utility itemsets with negative unit profits. Knowledge-Based Systems, 111, 283-298. https://doi.org/10.1016/j.knosys.2016.08.022
Liu, Y., Liao, W. K., & Choudhary, A. (2005). A fast high utility itemsets mining algorithm. In G. Weiss, M. Saar-Tsechansky, B. Zadrozny (Eds), Proceedings of the 1st international workshop on Utility-based data mining (pp. 90-99). Association for Computing Machinery, USA.
Vo, B., Nguyen, H., & Le, B. (2009). Mining high utility itemsets from vertical distributed databases. Paper presented at The 2009 IEEE-RIVF International Conference on Computing and Communication Technologies, Danang, Vietnam. http://doi.org/10.1109/RIVF.2009.5174650.
Yao, H., & Hamilton, H. J. (2006). Mining itemset utilities from transaction databases. Data & Knowledge Engineering, 59(3), 603-626. http://doi.org/10.1016/j.datak.2005.10.004
Yao, H., Hamilton, H. J., & Butz, C. J. (2004). A foundational approach to mining itemset utilities from databases. In M. W. Berry, U. Dayal, C. Kamath, & D. Skillicorn (Eds), Proceedings of the 2004 SIAM International Conference on Data Mining (pp. 482-486). Society for Industrial and Applied Mathematics, USA.
Zida, S., Fournier-Viger, P., Lin, J. C. W., Wu, C. W., & Tseng, V. S. (2017). EFIM: a fast and memory efficient algorithm for high-utility itemset mining. Knowledge and Information Systems, 51(2), 595-625. http://doi.org/10.1007/s10115-016-0986-0.
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Copyright (c) 2020 Cao Tùng Anh, Ngô Quốc Huy, Võ Hoàng Khanh.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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