Review on Optimization of Apriori Algorithm for Finding the Association Rules in Different Business and Other Datasets for Retrieval of Relations Between Different Entities

Authors

  • Prof. Pradeep N. Fale  Assistant Professor, Department of Information Technology, Priyadarshini College of Engineering, Nagpur, Maharashtra, India
  • Narendra Moundekar  Department of Information Technology, Priyadarshini College of Engineering, Nagpur, Maharashtra, India
  • RiteshSaudagar  Department of Information Technology, Priyadarshini College of Engineering, Nagpur, Maharashtra, India
  • Prajwal Kamdi  Department of Information Technology, Priyadarshini College of Engineering, Nagpur, Maharashtra, India
  • Mrunali Rode  Department of Information Technology, Priyadarshini College of Engineering, Nagpur, Maharashtra, India
  • Janvi Borkar  Department of Information Technology, Priyadarshini College of Engineering, Nagpur, Maharashtra, India

Keywords:

Customer Centric, Apriori Algorithm, Association Rules

Abstract

The secret of doing successful business lies in the accuracy of the decisions taken for the inventory management, production plans, being customer centric and being agile for the market developments. The business data processing for any business is huge one and may contain many hidden things, which must be revealed out intelligently and with optimization with respect to the time and other source constraints. Many times, it is beyond the scope of the human mind to figure out and relate the interdependencies of the multiple factors embedded in the business data and hence the machines could help in this context to make the task easy. When it comes to find the Association rules between different products of any shop or store, the Apriori algorithm tops the choice. The current review work depicts the attempts to use the Apriori algorithm in an optimized way and implementing the same according to the prevailing conditions.

References

  1. https://www.javatpoint.com/apriori-algorithm
  2. Ashish Shah,” Association Rule Mining with Modified Apriori Algorithm using Top down Approach”, 2nd International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT).
  3. Yi Cong, ”Research on Data Association Rules Mining Method based on Improved Apriori Algorithm”, International conference on Big Data and Artificial Intelligence and Software Engineering (ICBASE) 2020.
  4. Hanxiao Zhang, Wei Song, Lizhen Liu, Hanshi Wang,”The Application of Matrix Apriori Algorithm in Web Log Mining”, 2017 IEEE 2nd International Conference on Big Data Analysis.
  5. XU Hongfei , LIANG Xuesong , CUI Wei , LIU Wei,” Research on an Improved Association Rule Mining Algorithm”, International conference on Power Data Science (IPCDS) 2019, IEEE.
  6. Mohammad Javad ShayeganFard ,ParsaAsgariNamin,” Review of Apriori based Frequent Itemset Mining Solutions on Big Data”, 2020 6th International Conference on Web Research (ICWR) .
  7. Fulan Ye,” Research and Application of Improved APRIORI Algorithm Based on Hash Technology”, Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) 2020
  8. Hongqin Wang, HongxiaWang, Huiyong Jiang, Lina Yuan,”Research on an improved algorithm of Apriori based on Hadoop”, 2020 International Conference on Information Science, Parallel and Distributed Systems (ISPDS).
  9. Zhou Guojun. Study on multi-keyword sorting method based on HadoopJ]. Computer Engineering and Applications.2016, 52(17), pp.79-83. (in Chinese).
  10. CHEN Z F, FENG J. An optimized data mining algorithm based on Apriori algorithm J]. Computer and Modernization, 2016 (9). pp. 1-5. (in Chinese).
  11. Lin, X.: Mr-apriori: Association rules algorithm based on mapreduce. In Software Engineering and Service Science (ICSESS), 2014 5th IEEE international Conference on.pp.141-144.
  12. SUN Xuebo, SHI Feida. Research and optimization of Apriori algorithm based on Hadoop J]. Computer engineering and design.2018, 39(1), pp.126-133. (in Chinese).
  13. Agaoglu, Mustafa.Predicting Instructor Performance Using Data Mining Techniques in Higher EducationJ]. IEEE Access, 2017, pp.1-1
  14. Bin Chen, Peter Hass, Peter Scheuermann, “A New Two-Phase Sampling Based Algorithm for Discovering Association Rules”, SIGKDD '02 Edmonton, Albetra, Canada © 2002 ACM 1 58113 567 X/02/2007.
  15. Judith Pavón, Judith N, Viana S, and S mez,” Matrix apriori: speeding up the search for frequent patterns C]. Iasted” International Conference on Database and Applications. ACTA Press, pp 75—82, 2016.
  16. Hu J, Li B, ”An improved algorithm of association rules in the application of web logs J]”. Energy Procedia, 13, pp 1282̾1286, 2011.
  17. Wang Shuyan, Wang Xiaomei. Department of Computer, An X,“Application of Association Rules for Medical Data Classification J]”, Computer & Digital Engineering, 2009. 18J.Hu, A. Mojsilovic
  18. Duan Q, Li J, Wang Y,”The Application of Fuzzy Association Rule Mining in E-Commerce Information System Mining J]”, pp 631̾635, 2012.
  19. Agrawal, Imielinski, and Swami,“Mining Association Rules between Sets of Items of the ACM SIGMOG”, International Conference on Management of data, pp 207—216, 1993
  20. Goethals B,“Survey on Frequent Pattern MiningJ].”, Univ of Helsinki, 2003, 63(14):47-Lu Z, Yao Y, Zhong N. Web Log MiningJ]. Web Intelligence, 2003:173-194
  21. Guo Tao, Zhang Daiyuan,“Research and application of data mining association rules Apriori algorithm”, computer technology and development, 2011,06:101-103
  22. Wu Yugang, Qin Yong, Song Jiguang, Yang Zhongming,” Review of the research on Intrusion Detection Algorithm Based on association rules”, computer engineering and design, 2011,03:834-838
  23. Li Yuanbo, ”Tourism recommendation based on association rules algorithm” Shaanxi Normal University, 2015
  24. Yao Wendy,”Algorithm of association rules data mining research and application in Colleges and Universities Based on the achievements” ,Southwest Jiao Tong University, 2015
  25. Aman Chang, Li Lingjuan, “Research on Association Rule Mining Algorithm in cloud computing environment”, computer technology and development, 2011,02:43-46

International Journal of Scientific Research in Science, Engineering and Technology

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Published

2022-04-30

Issue

Volume 9, Issue 2, March-April-2022

Section

Research Articles

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How to Cite

[1]
Prof. Pradeep N. Fale, Narendra Moundekar, RiteshSaudagar, Prajwal Kamdi, Mrunali Rode, Janvi Borkar, " Review on Optimization of Apriori Algorithm for Finding the Association Rules in Different Business and Other Datasets for Retrieval of Relations Between Different Entities, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 2, pp.271-276, March-April-2022.