Behavior-based clustering and analysis of interestingness measures for association rule mining

DOI10.1007/s10618-013-0326-xzbMath1298.68230OpenAlexW2154663323MaRDI QIDQ468678

J. Herrera, Sumit K. Garg

Publication date: 7 November 2014

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10618-013-0326-x

zbMATH Keywords

clusteringassociation rule miningbehavior analysisinterestingness measures

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (7)

Critical appraisal of jointness concepts in Bayesian model averaging: evidence from life sciences, sociology, and other scientific fields ⋮ Calculating the relative importance of condition attributes based on the characteristics of decision rules and attribute reducts: application to crowdfunding ⋮ What to expect from a set of itemsets? ⋮ Scenario-based analysis for discovering relations among interestingness measures ⋮ Skopus: mining top-\(k\) sequential patterns under leverage ⋮ Visualizing the behavior and some symmetry properties of Bayesian confirmation measures ⋮ Time is money: dynamic-model-based time series data-mining for correlation analysis of commodity sales

Uses Software

• R
• UCI-ml
• ARVis
• GEMLeR

Cites Work

• Local equivalences of distances between clusterings -- a geometric perspective
• Combined use of association rules mining and clustering methods to find relevant links between binary rare attributes in a large data set
• ROC `n' rule learning -- towards a better understanding of covering algorithms
• Hierarchical clustering schemes
• Loevinger's measures of rule quality for assessing cluster stability
• On selecting interestingness measures for association rules: user oriented description and multiple criteria decision aid
• TESTS FOR RANK CORRELATION COEFFICIENTS. I
• The Interestingness Paradox in Pattern Discovery
• Discovery Science
• The amount of information that y gives about X
• Measures of Association for Cross Classifications
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