Enhanced mining association rule algorithm with reduced time & space complexity

Punit Mundra; Amit K. Maurya; Sanjay Singh

doi:10.1109/INDCON.2012.6420782

Enhanced mining association rule algorithm with reduced time & space complexity

Punit Mundra, Amit K. Maurya, Sanjay Singh

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	2012 Annual IEEE India Conference, INDICON 2012
Pages	1105-1110
Number of pages	6
DOIs	https://doi.org/10.1109/INDCON.2012.6420782
Publication status	Published - 01-12-2012
Event	2012 Annual IEEE India Conference, INDICON 2012 - Kochi, Kerala, India Duration: 07-12-2012 → 09-12-2012

Conference

Conference	2012 Annual IEEE India Conference, INDICON 2012
Country/Territory	India
City	Kochi, Kerala
Period	07-12-12 → 09-12-12

All Science Journal Classification (ASJC) codes

Software
Information Systems and Management
Control and Systems Engineering
Electrical and Electronic Engineering

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10.1109/INDCON.2012.6420782

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title = "Enhanced mining association rule algorithm with reduced time & space complexity",

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.",

author = "Punit Mundra and Maurya, {Amit K.} and Sanjay Singh",

year = "2012",

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doi = "10.1109/INDCON.2012.6420782",

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AU - Maurya, Amit K.

AU - Singh, Sanjay

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N2 - 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.

AB - 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.

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BT - 2012 Annual IEEE India Conference, INDICON 2012

T2 - 2012 Annual IEEE India Conference, INDICON 2012

Y2 - 7 December 2012 through 9 December 2012

ER -

Enhanced mining association rule algorithm with reduced time & space complexity

Abstract

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