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2005
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Optimizing Constraint-Based Mining by Automatically Relaxing Constraints

9 years 5 months ago
Optimizing Constraint-Based Mining by Automatically Relaxing Constraints
In constraint-based mining, the monotone and antimonotone properties are exploited to reduce the search space. Even if a constraint has not such suitable properties, existing algorithms can be re-used thanks to an approximation, called relaxation. In this paper, we automatically compute monotone relaxations of primitive-based constraints. First, we show that the latter are a superclass of combinations of both kinds of monotone constraints. Second, we add two operators to detect the properties of monotonicity of such constraints. Finally, we define relaxing operators to obtain monotone relaxations of them.
Arnaud Soulet, Bruno Crémilleux
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where ICDM
Authors Arnaud Soulet, Bruno Crémilleux
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