Quality Measures in Data Mining - Studies in Computational Intelligence
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Published By Springer Berlin Heidelberg

9783540449119, 9783540449188

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Understandability of Association Rules: A Heuristic Measure to Enhance Rule Quality

Quality Measures in Data Mining - Studies in Computational Intelligence ◽

10.1007/978-3-540-44918-8_8 ◽

2007 ◽

pp. 179-203

Author(s):

Rajesh Natarajan ◽

B. Shekar

Keyword(s):

Association Rules

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Association Rule Interestingness Measures: Experimental and Theoretical Studies

Quality Measures in Data Mining - Studies in Computational Intelligence ◽

10.1007/978-3-540-44918-8_3 ◽

2007 ◽

pp. 51-76 ◽

Cited By ~ 30

Author(s):

Philippe Lenca ◽

Benoît Vaillant ◽

Patrick Meyer ◽

Stephane Lallich

Keyword(s):

Association Rule ◽

Theoretical Studies ◽

Interestingness Measures ◽

Rule Interestingness ◽

Experimental And Theoretical Studies

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On the Discovery of Exception Rules: A Survey

Quality Measures in Data Mining - Studies in Computational Intelligence ◽

10.1007/978-3-540-44918-8_4 ◽

2007 ◽

pp. 77-98 ◽

Cited By ~ 6

Author(s):

Béatrice Duval ◽

Ansaf Salleb ◽

Christel Vrain

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Quality and Complexity Measures for Data Linkage and Deduplication

Quality Measures in Data Mining - Studies in Computational Intelligence ◽

10.1007/978-3-540-44918-8_6 ◽

2007 ◽

pp. 127-151 ◽

Cited By ~ 76

Author(s):

Peter Christen ◽

Karl Goiser

Keyword(s):

Data Linkage ◽

Complexity Measures

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A Graph-based Clustering Approach to Evaluate Interestingness Measures: A Tool and a Comparative Study

Quality Measures in Data Mining - Studies in Computational Intelligence ◽

10.1007/978-3-540-44918-8_2 ◽

2007 ◽

pp. 25-50 ◽

Cited By ~ 11

Author(s):

Xuan-Hiep Huynh ◽

Fabrice Guillet ◽

Julien Blanchard ◽

Pascale Kuntz ◽

Henri Briand ◽

...

Keyword(s):

Comparative Study ◽

Interestingness Measures ◽

Clustering Approach ◽

Graph Based Clustering

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Measuring and Modelling Data Quality for Quality-Awareness in Data Mining

Quality Measures in Data Mining - Studies in Computational Intelligence ◽

10.1007/978-3-540-44918-8_5 ◽

2007 ◽

pp. 101-126 ◽

Cited By ~ 7

Author(s):

Laure Berti-Équille

Keyword(s):

Data Mining ◽

Data Quality ◽

Quality Awareness ◽

Modelling Data

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Association Rule Interestingness: Measure and Statistical Validation

Quality Measures in Data Mining - Studies in Computational Intelligence ◽

10.1007/978-3-540-44918-8_11 ◽

2007 ◽

pp. 251-275 ◽

Cited By ~ 28

Author(s):

Stephane Lallich ◽

Olivier Teytaud ◽

Elie Prudhomme

Keyword(s):

Association Rule ◽

Statistical Validation ◽

Interestingness Measure ◽

Rule Interestingness

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Towards a Unifying Probabilistic Implicative Normalized Quality Measure for Association Rules

Quality Measures in Data Mining - Studies in Computational Intelligence ◽

10.1007/978-3-540-44918-8_10 ◽

2007 ◽

pp. 237-250 ◽

Cited By ~ 2

Author(s):

Jean Diatta ◽

Henri Ralambondrainy ◽

André Totohasina

Keyword(s):

Association Rules ◽

Quality Measure

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Statistical Methodologies for Mining Potentially Interesting Contrast Sets

Quality Measures in Data Mining - Studies in Computational Intelligence ◽

10.1007/978-3-540-44918-8_7 ◽

2007 ◽

pp. 153-177 ◽

Cited By ~ 7

Author(s):

Robert J. Hilderman ◽

Terry Peckham

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A New Probabilistic Measure of Interestingness for Association Rules, Based on the Likelihood of the Link

Quality Measures in Data Mining - Studies in Computational Intelligence ◽

10.1007/978-3-540-44918-8_9 ◽

2007 ◽

pp. 207-236 ◽

Cited By ~ 3

Author(s):

Israel-César Lerman ◽

Jérôme Azé

Keyword(s):

Association Rules ◽

Probabilistic Measure

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Quality Measures in Data Mining - Studies in Computational IntelligenceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Understandability of Association Rules: A Heuristic Measure to Enhance Rule Quality

Association Rule Interestingness Measures: Experimental and Theoretical Studies

On the Discovery of Exception Rules: A Survey

Quality and Complexity Measures for Data Linkage and Deduplication

A Graph-based Clustering Approach to Evaluate Interestingness Measures: A Tool and a Comparative Study

Measuring and Modelling Data Quality for Quality-Awareness in Data Mining

Association Rule Interestingness: Measure and Statistical Validation

Towards a Unifying Probabilistic Implicative Normalized Quality Measure for Association Rules

Statistical Methodologies for Mining Potentially Interesting Contrast Sets

A New Probabilistic Measure of Interestingness for Association Rules, Based on the Likelihood of the Link

Quality Measures in Data Mining - Studies in Computational Intelligence
Latest Publications