Framework for High Utility Pattern Mining using Dynamically Generated Minimum Support ThresholdFramework for High Utility Pattern Mining using Dynamically Generated Minimum Support Threshold

  • Authors

    • Shankar B. Naik
    • Jyoti D. Pawar
    2018-11-27
    https://doi.org/10.14419/ijet.v7i4.19.28276
  • Data mining, high utility itemset, data stream, closed itemset, frequent itemset.

  • Abstract

    In this paper we have proposed a framework which uses high utility itemset mining to store data stream elements in a compressed form and then detect events from the sliding window. This approach promises to reduce the memory requirements when applied to frequent pattern mining in data streams.

    In addition to this, a method to dynamically define the value of minimum support threshold based on data in the data stream is presented.

     

     

  • References

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  • How to Cite

    B. Naik, S., & D. Pawar, J. (2018). Framework for High Utility Pattern Mining using Dynamically Generated Minimum Support ThresholdFramework for High Utility Pattern Mining using Dynamically Generated Minimum Support Threshold. International Journal of Engineering & Technology, 7(4.19), 1007-1010. https://doi.org/10.14419/ijet.v7i4.19.28276

    Received date: 2019-03-10

    Accepted date: 2019-03-10

    Published date: 2018-11-27