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High Utility Association Rule Mining

  • Loan T. T. NguyenEmail author
  • Thang Mai
  • Bay Vo
Chapter
Part of the Studies in Big Data book series (SBD, volume 51)

Abstract

Most businesses focus on the profits. For example, supermarkets often analyze sale activities to investigate which products bring the most revenue, as well as find out customer trends based on their carts. To achieve this, a number of studies have examined high utility itemsets (HUIs). Traditional association rule mining algorithms only generate a set of highly frequent rules, but these rules do not provide useful answers for what the high utility association rules are. This chapter provides overview current approaches to mine high utility association rules.

References

  1. 1.
    Agrawal, R., Imielinski, T., Swami, A.: Mining association rules between sets of items in large databases. In: Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, pp. 207–216 (1993)Google Scholar
  2. 2.
    Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In: VLDB 1994, pp. 487–499 (1994)Google Scholar
  3. 3.
    Choi, V.: Faster algorithms for constructing a concept (Galois) lattice (2006). arXiv:cs.DM/0602069
  4. 4.
    Duong, H.V., Truong, T.C., Vo, B.: An efficient method for mining frequent itemsets with double constraint. Eng. Appl. Artif. Intell. 27, 148–154 (2014)CrossRefGoogle Scholar
  5. 5.
    Fournier-Viger, P., Wu, C., Zida, S., Tseng, V.S.: Faster high utility itemset mining using estimated utility co-occurrence pruning. In: Proceedings 21st International Symposium on Methodologies for Intelligent Systems, pp. 83–92 (2014)Google Scholar
  6. 6.
    Gan, W., Lin, J.C., Fournier-Viger, P., Chao, H.: More Efficient Algorithms for Mining High-Utility Itemsets with Multiple Minimum Utility Thresholds. DEXA(1), 71–87 (2016)Google Scholar
  7. 7.
    Grahne, G., Zhu, J.: Fast algorithms for frequent itemset mining using FP-trees. IEEE Trans. Knowl. Data Eng. 17(10), 1347–1362 (2005)CrossRefGoogle Scholar
  8. 8.
    Liu, Y., Liao, W., Choudhary, A.: A two-phase algorithm for fast discovery of high utility itemsets. In: Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining, pp. 689–695 (2005)CrossRefGoogle Scholar
  9. 9.
    Liu, M., Qu, J.: Mining high utility itemsets without candidate generation. In: Proceedings of the 21st ACM international conference on Information and knowledge management, pp. 55–64 (2012)Google Scholar
  10. 10.
    Mai, T., Vo, B., Nguyen, L.T.T.: A lattice-based approach for mining high utility association rules. Inf. Sci. 399, 81–97 (2017)CrossRefGoogle Scholar
  11. 11.
    Nguyen, D., Nguyen, L.T.T., Vo, B., Pedrycz, W.: Efficient mining of class association rules with the itemset constraint. Knowl. Based Syst. 103, 73–88 (2016)CrossRefGoogle Scholar
  12. 12.
    Nguyen, D., Vo, B., Le, B.: CCAR: an efficient method for mining class association rules with itemset constraints. Eng. Appl. Artif. Intell. 37, 115–124 (2015)CrossRefGoogle Scholar
  13. 13.
    Priss, U.: Lattice-based information retrieval. Knowl. Organ. 27(3), 132–142 (2000)Google Scholar
  14. 14.
    Sahoo, J., Das, A.K., Goswami, A.: An effective association rule mining scheme using a new generic basis. Knowl. Inf. Syst. 43(1), 127–156 (2015)CrossRefGoogle Scholar
  15. 15.
    Sahoo, J., Das, A.K., Goswami, A.: An efficient approach for mining association rules from high utility itemsets. Expert Syst. Appl. 42(13), 5754–5778 (2015)CrossRefGoogle Scholar
  16. 16.
    Tseng, V.S., Wu, C., Fournier-Viger, P., Yu, P.S.: Efficient algorithms for mining top-K high utility itemsets. IEEE Trans. Knowl. Data Eng. 28(1), 54–67 (2016)CrossRefGoogle Scholar
  17. 17.
    Tseng, V.S., Wu, C., Shie, B., Yu, P.S.: P-Growth: an efficient algorithm for high utility itemset minin. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 253–262 (2010)Google Scholar
  18. 18.
    Tseng, V.S., Wu, C., Shie, B., Yu, P.S.: Efficient algorithms for mining high utility itemsets from transactional databases. IEEE Trans. Knowl. Data Eng. 25(8), 1772–1786 (2013)CrossRefGoogle Scholar
  19. 19.
    Vo, B., Hong, T., Le, B.: A lattice-based approach for mining most generalization association rules. Knowl. Based Syst. 45, 20–30 (2013)CrossRefGoogle Scholar
  20. 20.
    Vo, B., Le, B.: Mining traditional association rules using frequent itemsets lattice. In: 39th International Conference on Computers and Industrial Engineering, pp. 1401–1406 (2009)Google Scholar
  21. 21.
    Vo, B., Le, B.: Mining minimal non-redundant association rules using frequent itemsets lattice. J. Intell. Syst. Technol. Appl. 10(1), 92–106 (2011a)Google Scholar
  22. 22.
    Vo, B., Le, B.: Interestingness for association rules: combination between lattice and hash tables. Expert Syst. Appl. 38(9), 11630–11640 (2011)CrossRefGoogle Scholar
  23. 23.
    Vo, B., Nguyen, H., Le, B.: Mining high utility itemsets from vertical distributed databases. In: International Conference Computing and Communication Technologies, pp. 1–4 (2009)Google Scholar
  24. 24.
    Vo, B., Le, T., Pedrycz, W., Nguyen, G., Baik, S.W.: Mining erasable itemsets with subset and superset itemset constraints. Expert Syst. Appl. 69, 50–61 (2017)CrossRefGoogle Scholar
  25. 25.
    Yun, U., Ryang, H., Ryu, K.H.: High utility itemset mining with techniques for reducing overestimated utilities and pruning candidates. Expert Syst. Appl. 41(8), 3861–3878 (2014)CrossRefGoogle Scholar
  26. 26.
    Zaki, M.J., Hsiao, C.J.: Efficient algorithms for mining closed itemsets and their lattice structure. IEEE Trans. Knowl. Data Eng. 17(4), 462–478 (2005)CrossRefGoogle Scholar
  27. 27.
    Zida, S., Fournier-Viger, P., Lin, J.W., Wu, C., Tseng, V.S.: EFIM: A Fast and Memory Efficient Algorithm for High-Utility Itemset Minin. Knowl. Inf. Syst. 51(2), 595–625 (2017)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Computer Science and EngineeringInternational University - Vietnam National UniversityHo Chi Minh CityVietnam
  2. 2.Faculty of Information TechnologyHo Chi Minh City University of Technology (HUTECH)Ho Chi Minh CityVietnam

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