DocumentCode :
3083280
Title :
Enhanced mining association rule algorithm with reduced time & space complexity
Author :
Mundra, Punit ; Maurya, K. ; Singh, Sushil
Author_Institution :
Dept. of Inf. & Commun. Technol., Manipal Univ., Manipal, India
fYear :
2012
fDate :
7-9 Dec. 2012
Firstpage :
1105
Lastpage :
1110
Abstract :
In this paper, we have proposed a technique to improve the performance of existing mining association rule algorithm which significantly reduces the time and space complexity of independent of datasets. There are many data mining algorithms for finding association rules our contribution can be used in almost all of the algorithms independent of its variety. In this paper we are concentrating more on Apriori algorithm which is a type of candidate generation algorithm also a fundamental block of all the mining algorithms, rectifying its major limitation of consuming ample amount of time in generating the candidates.
Keywords :
computational complexity; data mining; a priori algorithm; data mining algorithm; mining association rule algorithm; space complexity reduction; time complexity reduction; Arrays; Association rules; Indexes; Time complexity; Association Rule; Candidate Generation Algorithm; Data Mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
India Conference (INDICON), 2012 Annual IEEE
Conference_Location :
Kochi
Print_ISBN :
978-1-4673-2270-6
Type :
conf
DOI :
10.1109/INDCON.2012.6420782
Filename :
6420782
Link To Document :
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