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» Ontology Mapping based on Association Rule Mining
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GFKL
2006
Springer
75views Data Mining» more  GFKL 2006»
13 years 11 months ago
Classification of Contradiction Patterns
Abstract. Solving conflicts between overlapping databases requires an understanding of the reasons that lead to the inconsistencies. Provided that conflicts do not occur randomly b...
Heiko Müller, Ulf Leser, Johann Christoph Fre...
DBA
2006
182views Database» more  DBA 2006»
13 years 8 months ago
Matrix Apriori: Speeding Up the Search for Frequent Patterns
This work discusses the problem of generating association rules from a set of transactions in a relational database, taking performance and accuracy of found results as the essent...
Judith Pavón, Sidney Viana, Santiago G&oacu...
SEMWEB
2007
Springer
14 years 1 months ago
OntoDNA: Ontology Alignment Results for OAEI 2007
OntoDNA is an automated ontology mapping and merging system that utilizes unsupervised data mining methods, comprising of Formal Concept analysis (FCA), Self-Organizing map (SOM) a...
Ching-Chieh Kiu, Chien-Sing Lee
DEXA
2008
Springer
123views Database» more  DEXA 2008»
13 years 9 months ago
Emerging Pattern Based Classification in Relational Data Mining
The usage of descriptive data mining methods for predictive purposes is a recent trend in data mining research. It is well motivated by the understandability of learned models, the...
Michelangelo Ceci, Annalisa Appice, Donato Malerba
PKDD
2009
Springer
134views Data Mining» more  PKDD 2009»
14 years 1 months ago
Mining Graph Evolution Rules
In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level. Given a sequenc...
Michele Berlingerio, Francesco Bonchi, Björn ...