R.  Anuradha, N.  Rajkumar, 
    Mining a Complete Set of Fuzzy Multiple-Level Coherent Rules,
    Asian Journal of Information Technology,
    Volume 15,Issue 18,
    2016,
    Pages 3441-3448,
    ISSN 1682-3915,
    ajit.2016.3441.3448,
    (https://makhillpublications.co/view-article.php?doi=ajit.2016.3441.3448)
    Abstract: Data-mining techniques are developed to transform raw data into suitable knowledge-oriented data.
The algorithms for mining association rules identify relationships among transactions using interesting
measures like support and confidence at a single-concept level or multiple levels. Using support and confidence
alone for mining associations would not give interesting rules both for quantitative as well as binary data. This
study proposes a fuzzy coherent rule mining algorithm at multi-level hierarchies to discover the significant rules
in quantitative transactions. The proposed method combines fuzzy coherent rules mining concept with that of
taxonomical mining in a quantitative database. The algorithm works on a top down methodology in traversing
the data that exists in a hierarchical form. An experimental comparison with the fuzzy coherent rule mining
methodology conveys the significance of the proposed algorithm in finding the level-wise coherent rules.
    Keywords: Association rules;fuzzy coherent rule;quantitative database;membership;function