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An Improved Evaluation Methodology for Mining Association Rules
Axioms, 2021 At present, association rules have been widely used in prediction, personalized recommendation, risk analysis and other fields. However, it has been pointed out that the traditional framework to evaluate association rules, based on Support and Confidence
Fuguang Bao +4 more
semanticscholar +1 more source
Numerical Association Rule Mining from a Defined Schema Using the VMO Algorithm
Applied Sciences, 2021 Association rule mining has been studied from various perspectives, all of which have made valuable contributions to data science. However, there are promising research lines, such as the inclusion of continuous variables and the combination of numerical
Iván Fredy Jaramillo +2 more
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Proposed Parallel Association Rules Algorithm [PDF]
Engineering and Technology Journal, 2014 Data mining is an advanced technique for extracting knowledge from a large amount of data for classification, prediction, estimation, clustering or association rules or any activities, which need decision.
Emad kadhiem Jabbar +1 more
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Mining Hierarchical Negative Association Rules [PDF]
International Journal of Computational Intelligence Systems, 2012 The negative association between items in databases is as important and interesting as the positive one. But, it has not been studied as much. We consider negative association in a hierarchical setting, in which we are able to generate negative ...
David Taniar +3 more
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Efficient Mining Support-Confidence Based Framework Generalized Association Rules
Mathematics, 2022 Mining association rules are one of the most critical data mining problems, intensively studied since their inception. Several approaches have been proposed in the literature to extend the basic association rule framework to extract more general rules ...
Amira Mouakher +2 more
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Selective association rule generation [PDF]
Computational Statistics, 2007 Mining association rules is a popular and well researched method for discovering interesting relations between variables in large databases. A practical problem is that at medium to low support values often a large number of frequent itemsets and an even larger number of association rules are found in a database.
Hahsler, Michael +2 more
openaire +3 more sources
Recommendation with quantitative implication rules [PDF]
EAI Endorsed Transactions on Context-aware Systems and Applications, 2019 Association rules based recommendation is one of approaches to develop recommendation systems. However, such systems just focus on binary dataset, whereas many datasets are in the quantitative form. There are many solutions proposed for this problem such
Hoang Nguyen +3 more
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Closed Association Rules [PDF]
Annales Mathematicae et Informaticae, 2020 Summary: In this paper we present a new basis for association rules called Closed Association Rules (\(\mathcal{CR}\)). This basis contains all valid association rules that can be generated from frequent closed itemsets. \(\mathcal{CR}\) is a lossless representation of all association rules.
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SALES LEVEL ANALYSIS USING THE ASSOCIATION METHOD WITH THE APRIORI ALGORITHM
Jurnal Riset Informatika, 2022 The company does not yet know the pattern of consumer purchases because so far, the sales transaction data has not been used correctly and does not have a unique method to determine consumer buying patterns.
Samuel Samuel +4 more
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Lietuvos Matematikos Rinkinys, 2004 The secondary outcome of implementing the computerized application process for -studies at Lithuania's institutions of higher education is the availability of the collected data.
Ieva Mitašiūnaitė +1 more
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