DocumentCode :
721228
Title :
Implementation of coherent rule mining algorithm for association rule mining
Author :
Davale, Aditya A. ; Shende, Shailendra W.
Author_Institution :
Dept. of Inf. Technol., Yeshwantrao Chavan Coll. of Eng., Nagpur, India
fYear :
2015
fDate :
25-27 Feb. 2015
Firstpage :
538
Lastpage :
541
Abstract :
In the data mining field, association rules are generated from domain knowledge which is evaluated from the minimum support threshold value. The accuracy in setting up this threshold directly influences the number and the quality of association rules discovered. The number of association rules discovered is large in numbers but still misses some interesting rules and the rule´s quality. So, the solution to this is the use of propositional logic to generate the association rules to avoid loss of rules. Coherent rules are discovered from the propositional logic so it does not require the domain expert. The coherent rules are discovered without knowing the value of minimum threshold. So, there is no need of deciding the threshold value. The results are compared with results apriori algorithm.
Keywords :
data mining; formal logic; association rule mining; coherent rule mining algorithm; data mining; domain expert; minimum support threshold value; minimum threshold; propositional logic; Algorithm design and analysis; Animals; Association rules; Classification algorithms; Dairy products; Market research; association rules; data mining; support;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE), 2015 International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-8432-9
Type :
conf
DOI :
10.1109/ABLAZE.2015.7154920
Filename :
7154920
Link To Document :
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