TY  - JOUR
T1  - Mining a Complete Set of Fuzzy Multiple-Level Coherent Rules
AU - Anuradha, R. AU - Rajkumar, N. 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 18
SP  - 3441
EP  - 3448
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.3441.3448
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.3441.3448
KW  - Association rules
KW  -fuzzy coherent rule
KW  -quantitative database
KW  -membership
KW  -function
AB  - 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.
ER  -