Front Inner Page - Volume 4 No.3 June 2017

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  • Title

    :

    FiDoop Parallel Mining of Frequent Item sets Using MapReduce

    Authors

    :

    G. Sudha 1, K. Kavitha2

    Keywords

    :

    FiDoop, Map Reduce Clustering, Frequency set mining, support and confidence.

    Issue Date

    :

    June 2017

    Abstract

    :

    Due to the exponential increase of real-time data monitoring systems, the extraction of frequent item (Frequent item set mining) set from large uncertain database is the challenging task. The existing parallel mining algorithm for frequent item sets includes the limitations in terms of more memory usage and excessive run time even for less amount of data. To overcome this problem, the FiDoop based item set mining algorithm is proposed by using map reduce framework. It is used to improve the performance of load balancing operation in an uncertain database for computing frequent patterns. This system includes data uploading, preprocessing, threshold, find support and confidence, merge and result. Initially, the data is selected from the dataset and uploaded in the server.

    Page(s)

    :

    1-6

    ISSN

    :

    2347- 4734

    Source

    :

    Vol. 4, No.3, June 2017

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