Volume 7 Issue 3 - September 2016

  • 1. Frame work for association rule mining with updated fp-growth and modified cofi approaches

    Authors : Pdvn Kumar

    Pages : 11-20

    DOI : http://dx.doi.org/10.21172/1.73.502

    Keywords : Association Rule, Frequent Item Set, FP-tree, COFI-tree, Ordered-Partitioning Bases, Leap Traversal approach

    Abstract :

    Association rules are interesting correlations among attributes in a database. The discovery of association rules is an extremely computationally expensive task and it is therefore imperative to have fast scalable algorithms for mining these rules. In this paper, we present efficient techniques for discovering association rules from large databases and for removing redundancy from these rules so as to improve the quality of output. Some of the important algorithms that can be considered for Association Mining are FP-Growth and COFI algorithm. FP-Growth algorithm generates frequent item sets from an FP-tree by exploring the tree in a bottom-up fashion. The COFI algorithm is not only one order of magnitude faster and requires significantly less memory than the FP-Growth; it is also very effective with extremely large datasets

    Citing this Journal Article :

    Pdvn Kumar, "Frame work for association rule mining with updated fp-growth and modified cofi approaches", https://www.ijltet.org/journal_details.php?id=907&j_id=3311, Volume 7 Issue 3 - September 2016, 11-20, #ijltetorg