@article{MAKHILLAJIT201615186369,
    title = {Mining a Complete Set of Fuzzy Multiple-Level Coherent Rules},
    journal = {Asian Journal of Information Technology},
    volume = {15},
    number = {18},
    pages = {3441-3448},
    year = {2016},
    issn = {1682-3915},
    doi = {ajit.2016.3441.3448},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2016.3441.3448},
    author = {R. and},
    keywords = {Association rules,fuzzy coherent rule,quantitative database,membership,function},
    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.}
    }