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2008•Journal of Chengdu University of Information TechnologyRequires access

An improved algorithm for mining association rules with weighted items

Wei Qian

Open publisher page 1 citations

Abstract

The mining association rules are widely used in many fields and lots of algorithms are presented.Most of these algorithms treat each item as an uniformity.However in the practical applications the importance of the items is different.The decision-makers are more inclined to items whose profits are higher than others.The shortages of the existing algorithms for the mining weighted association rules are analyzed and a new weighted association rule model is given.

About this research paper

What this paper is about

The mining association rules are widely used in many fields and lots of algorithms are presented.Most of these algorithms treat each item as an uniformity.However in the practical applications the importance of the items is different.The decision-makers are more inclined to items whose profits are higher than others.The shortages of the existing algorithms for the mining weighted association rules are analyzed and a new weighted association rule model is given.

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OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The mining association rules are widely used in many fields and lots of algorithms are presented.Most of these algorithms treat each item as an uniformity.However in the practical applications the importance of the items is different.The decision-makers are more inclined to items whose profits are higher than others.The shortages of the existing algorithms for the mining weighted association rules are analyzed and a new weighted association rule model is given.

Key concepts: Association rule learning, Economic shortage, Computer science, Apriori algorithm, Association (psychology), Data mining, Algorithm, Government (linguistics)

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