Abstract
In this paper, we thus present an algorithm to efficiently update the multiple fuzzy frequent itemsets from the quantitative dataset with transaction insertion. The designed approach is based on the Fast UPdated (FUP) concept to divide the transformed linguistic terms into four cases, and each case is performed by the designed approach for updating the discovered information. Also, the fuzzy-list (FL) structure is adopted to reduce the generation of candidates without multiple database scans. Experiments are conducted to show that the proposed algorithm outperforms the state-of-the-art approach.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: International Conference on Very Large Data Bases, pp. 487–499 (1994)
Cheung, D.W., Wong, C.Y., Han, J., Ng, V.T.: Maintenance of discovered association rules in large databases: an incremental updating techniques. In: The International Conference on Data Engineering, pp. 106–114 (1996)
Delgado, M., Marin, N., Sanchez, D., Vila, M.A.: Fuzzy association rules: general model and applications. IEEE Trans. Fuzzy Syst. 11, 214–225 (2003)
Fournier-Viger, P., Lin, J.C.W., Gomariz, A., Gueniche, T., Soltani, A., Deng, Z., Lam, H.T.: The SPMF open-source data mining library version 2 and beyond. In: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery, pp. 36–40 (2016)
Han, J., Jian, P., Yin, Y., Mao, R.: Mining frequent patterns without candidate generation: a frequent-pattern tree approach. Data Min. Knowl. Disc. 8(1), 53–87 (2004)
Hong, T.P., Kuo, C.S., Chi, S.C.: Mining association rules from quantitative data. Intell. Data Anal. 3(5), 363–376 (1999)
Hong, T.P., Lin, C.W., Wu, Y.L.: Incrementally fast updated frequent pattern trees. Expert Syst. Appl. 34(4), 2424–2435 (2008)
Hong, T.P., Lan, G.C., Lin, Y.H., Pan, S.T.: An effective gradual data-reduction strategy for fuzzy itemset mining. Int. J. Fuzzy Syst. 15(2), 170–181 (2013)
Hong, T.P., Lin, C.W., Lin, T.C.: The MFFP-tree fuzzy mining algorithm to discover complete linguistic frequent itemsets. Comput. Intell. 30(1), 145–166 (2014)
Kuok, C.M., Fu, A., Wong, M.H.: Mining fuzzy association rules in databases. ACM SIGMOD Rec. 27(1), 41–46 (1998)
Lin, C.W., Hong, T.P., Lu, W.H.: Linguistic data mining with fuzzy fp-trees. Expert Syst. Appl. 37(6), 4560–4567 (2010)
Lin, C.W., Hong, T.P., Lin, T.C.: An efficient tree-based fuzzy data mining approach. Int. J. Fuzzy Syst. 12(2), 150–157 (2010)
Lin, C.W., Hong, T.P., Lu, W.H.: Mining fuzzy frequent itemsets based on UBFFP trees. J. Intell. Fuzzy Syst. 27(1), 535–548 (2014)
Lin, J.C.W., Hong, T.P., Lin, T.C.: A CMFFP-tree algorithm to mine complete multiple fuzzy frequent itemsets. Appl. Soft Comput. 28(C), 431–439 (2015)
Lin, J.C.W., Hong, T.P., Lin, T.C., Pan, S.T.: An UBMFFP tree for mining multiple fuzzy frequent itemsets. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 23(6), 861–879 (2015)
Lin, J.C.W., Li, T., Fournier-Viger, P., Hong, T.P., Wu, J.M.T., Zhan, J.: Efficient mining of multiple fuzzy frequent itemsets. Int. J. Fuzzy Syst. 19(4), 1032–1040 (2017)
Shitong, W., Chung, K.F.L., Hongbin, S.: Fuzzy taxonomy, quantitative database and mining generalized association rules. Intell. Data Anal. 9(2), 207–217 (2005)
Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)
Acknowledgment
This research was partially supported by the National Natural Science Foundation of China (NSFC) under grant No. 61503092 and by the Research on the Technical Platform of Rural Cultural Tourism Planning Basing on Digital Media under grant 2017A020220011.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Wu, TY., Lin, J.CW., Zhang, Y. (2018). Mining of Multiple Fuzzy Frequent Itemsets with Transaction Insertion. In: Krömer, P., Alba, E., Pan, JS., Snášel, V. (eds) Proceedings of the Fourth Euro-China Conference on Intelligent Data Analysis and Applications. ECC 2017. Advances in Intelligent Systems and Computing, vol 682. Springer, Cham. https://doi.org/10.1007/978-3-319-68527-4_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-68527-4_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-68526-7
Online ISBN: 978-3-319-68527-4
eBook Packages: EngineeringEngineering (R0)