Abstract
In this paper, the association rule is elaborated on the basis of Apriori taking the diabetic patient’s disease record as a case. The core idea of association rule on the basis of Apriori algorithm for mining large item sets is discussed, furthermore the example shows the execution process of the algorithm.
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
Hájek, Petr, Ivan Havel, and Metoděj Chytil. 1966. The GUHA method of automatic hypotheses determination. Computing 1 (4): 293–308.
Agrawal, R., T. Imieliński, and A. Swami. 1993. Mining association rules between sets of items in large databases. In Proceedings of the 1993 ACM SIGMOD international conference on Management of data—SIGMOD ’93, 207.
Agrawal, R. 1994. Fast algorithms for mining association rules in large databases. In Proceedings of the 20th international conference on very large data bases (VLDB), 478–499.
Lei, Z, Z. Zi-dong, W. Xiao-dong et al. 2009. The applied research of association rules mining in automobile industry. WRI World Congress on computer science and information engineering. IEEE 4: 241–245.
Tie, Xu. 2010. Processing and analysis of residents travel survey data based on association rules. WASE international conference on information engineering. IEEE 3: 377–380.
Mohapatra, D.P., and S. Patnaik. 2013. Intelligent computing, networking, and informatics. Advances in Intelligent Systems & Computing 243: 1047–1054.
Jung, H., and K.Y. Chung. 2014. Mining-based associative image filtering using harmonic mean. Cluster Computing 17 (3): 767–774.
Liu, Z, Q. Shen, and J. Ma. 2018. Extracting implicit features based on association rules. In Proceedings of the 3rd international conference on crowd science and engineering. ACM, 18.
Liu, J., L. Yinan, and Z. Ting. 2012. The analysis and evaluation on heavy metal pollution of topsoil in Chinese large-scale cities. Energy Procedia 16: 1084–1089.
Yanhua T. A discovery for the association rules of operation sequence based on improved Apriori algorithm. In Software engineering and knowledge engineering: Theory and practice, 399–405 Springer, Berlin, and Heidelberg.
Hemalatha, M. 2012. Market basket analysis—A data mining application in Indian retailing. International Journal of Business Information Systems 10 (1): 109–129.
Acknowledgements
This research was supported by 2018 Funds for basic scientific research in Heilongjiang Province (project number: 2018-KYYWFMY-0096).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Wang, X., Su, K., Liu, Z. (2020). Analysis of Diabetic Association Rules Based on Apriori Algorithms. In: Huang, C., Chan, YW., Yen, N. (eds) Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019). Advances in Intelligent Systems and Computing, vol 1088. Springer, Singapore. https://doi.org/10.1007/978-981-15-1468-5_67
Download citation
DOI: https://doi.org/10.1007/978-981-15-1468-5_67
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-1467-8
Online ISBN: 978-981-15-1468-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)