Modified classic apriori algorithm for association rule mining

  • Authors

    • G Anitha
    • R A. Karthika
    • G Bindu
    • G V. Sriramakrishnan
    2018-04-20
    https://doi.org/10.14419/ijet.v7i2.21.12455
  • Apriori, frequent itemset, support, confidence, candidate itemset.

  • Abstract

    In today’s real world environment, information is the most critical element in all aspects of the life. It can be used to perform analysis and it helps to make decision making. But due to large collection of information the analysis and extraction of such useful information is tedious process which will create a major problem. In data mining, Association rules states about associations among the entities of known and unknown group and extracting hidden patterns in the data. Apriori algorithm is used for association rule mining. In this paper, due to limitations in rule condition, the algorithm was extended as new modified classic apriori algorithm which fulfills user stated minimum support and confidence constraints.

     

     

  • References

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  • How to Cite

    Anitha, G., A. Karthika, R., Bindu, G., & V. Sriramakrishnan, G. (2018). Modified classic apriori algorithm for association rule mining. International Journal of Engineering & Technology, 7(2.21), 414-416. https://doi.org/10.14419/ijet.v7i2.21.12455

    Received date: 2018-05-04

    Accepted date: 2018-05-04

    Published date: 2018-04-20