Abstract
Aiming to improve the security of large database in cloud storage space, a hierarchical mining algorithm of spatial big data set association rules based on association dimension feature detection is proposed. The statistical characteristic quantity of large spatial data set is constructed by means of group sample regression analysis, and the sampling and sample recognition of spatial big data set are carried out by using fuzzy rough set mapping method. The association rule distribution model of large spatial datasets is constructed by using the hierarchical mining method of association rules, and the feature quantities of association rules are extracted from large spatial datasets. The correlation dimension feature extraction algorithm is used to optimize the extraction process of large spatial data sets adaptively, so as to realize the hierarchical mining optimization of spatial big data set association rules. The simulation results show that the proposed method has higher accuracy, higher mining accuracy and better feature matching ability, which improves the mining ability of association rules in large database in cloud storage space.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Muramatsu, M.: On network simplex method using the primal-dual symmetric pivoting rule. J. Oper. Res. Soc. Jpn. 43(1), 149–161 (2017)
Ma, Z., Chen, W.: Friction torque calculation method of ball bearings based on rolling creepage theory. J. Mech. Eng. 53(22), 219–224 (2017)
Tu, G., Yang, X., Zhou, T.: Efficient identity-based multi-identity fully homomorphic encryption scheme. J. Comput. Appl. 39(3), 750–755 (2019)
Wang, Z., Huang, M., et al.: Integrated algorithm based on density peaks and density-based clustering. J. Comput. Appl. 39(2), 398–402 (2019)
Helmy, A., Hedayat, A., Al-Dhahir, N.: Robust weighted sum-rate maximization for the multi-stream MIMO interference channel with sparse equalization. IEEE Trans. Commun. 60(10), 3645–3659 (2015)
Alfaro, V.M., Vilanovab, R.: Robust tuning of 2DoF five-parameter PID controllers for inverse response controlled processes. J. Process Control 23(4), 453–462 (2013)
Han, D., Chen, X., Lei, Y., et al.: Real-time data analysis system based on spark streaming and its application. J. Comput. Appl. 37(5), 1263–1269 (2017)
Sun, D.W., Zhang, G.Y., Zheng, W.M.: Big data stream computing, technologies and instances. J. Softw. 25(4), 839–862 (2014)
Hao, S.G., Zhang, L., Muhammad, G.: A union authentication protocol of cross-domain based on bilinear pairing. J. Softw. 8(5), 1094–1100 (2013)
Zhu, Y., Zhu, X., Wang, J.: Time series motif discovery algorithm based on subsequence full join and maximum clique. J. Comput. Appl. 39(2), 414–420 (2019)
Wang, Z., Zheng, Q., Chen, C., et al.: Virtual network mapping algorithm based on network simplex. Comput. Eng. 45(4), 13–17 (2019)
Wang, I.L., Lin, S.J.: A network simplex algorithm for solving the minimum distribution cost problem. J. Ind. Manag. Optim. 5(4), 929–950 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Wang, Y., Song, W. (2019). Research on Hierarchical Mining Algorithm of Spatial Big Data Set Association Rules. In: Gui, G., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-030-36405-2_21
Download citation
DOI: https://doi.org/10.1007/978-3-030-36405-2_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-36404-5
Online ISBN: 978-3-030-36405-2
eBook Packages: Computer ScienceComputer Science (R0)