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A Proposed Method to Select Potential Item Set for High Utility Item Set Mining using Genetic Algorithm Techniques

Pradeep Sharma, Ruchika Pachori, RajLaxmi Garg. Published in Algorithms.

Communications on Applied Electronics
Year of Publication: 2017
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Pradeep Sharma, Ruchika Pachori, RajLaxmi Garg
10.5120/cae2017652542

Pradeep Sharma, Ruchika Pachori and RajLaxmi Garg. A Proposed Method to Select Potential Item Set for High Utility Item Set Mining using Genetic Algorithm Techniques. Communications on Applied Electronics 6(8):35-40, March 2017. BibTeX

@article{10.5120/cae2017652542,
	author = {Pradeep Sharma and Ruchika Pachori and RajLaxmi Garg},
	title = {A Proposed Method to Select Potential Item Set for High Utility Item Set Mining using Genetic Algorithm Techniques},
	journal = {Communications on Applied Electronics},
	issue_date = {March 2017},
	volume = {6},
	number = {8},
	month = {Mar},
	year = {2017},
	issn = {2394-4714},
	pages = {35-40},
	numpages = {6},
	url = {http://www.caeaccess.org/archives/volume6/number8/715-2017652542},
	doi = {10.5120/cae2017652542},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Utility mining is a technique to prune high utility itemset from the given transactional database on the basis of user-defined minimum utility threshold. Frequent itemset mining, only focus on itemset appear most frequently in the database while in utility mining we concern about utility i.e. importance or profit of itemset according to the user preference. In this paper we are proposing a two-phase algorithm, in the first phase, we are using weighted transaction utility concept to calculate and compare the utility of itemset with minimum utility threshold and then in the second phase, we are proposing genetic algorithm technique to search high utility itemset from the recognized transactional database obtain after the first phase.

References

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Keywords

Data Mining, Weighted Transaction Utility, Utility Mining, Genetic Algorithm.