A fuzzy data mining algorithm for quantitative values

This paper attempts to propose a new data-mining algorithm to enhance the capability of exploring interesting knowledge from transactions with quantitative values. The proposed algorithm integrates the fuzzy set concepts and the a priori mining algorithm to find interesting fuzzy association rules f...

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Bibliographic Details
Published in1999 Third International Conference on Knowledge-Based Intelligent Information Engineering Systems. Proceedings (Cat. No.99TH8410) pp. 480 - 483
Main Authors Tzung-Pei Hong, Chan-Sheng Kuo, Sheng-Chai Chi
Format Conference Proceeding
LanguageEnglish
Published IEEE 1999
Subjects
Algorithm design and analysis
Association rules
Data mining
Electronic mail
Filtering algorithms
Fuzzy sets
Humans
Information management
Itemsets
Knowledge management
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Summary:This paper attempts to propose a new data-mining algorithm to enhance the capability of exploring interesting knowledge from transactions with quantitative values. The proposed algorithm integrates the fuzzy set concepts and the a priori mining algorithm to find interesting fuzzy association rules from given transaction data. Experiments on student grades in I-Shou University are also made to verify the performance of the proposed algorithm.
ISBN:9780780355781
0780355784
DOI:10.1109/KES.1999.820227