document: Characterising the difference Characterising the differences between two databases is an often occurring problem in Data Mining . Detection of change over time is a prime example , comparing databases from two branches is another one . The key problem is to discover the patterns that describe the difference . Emerging patterns provide only a partial answer to this question . In previous work , we showed that the data distribution can be captured in a pattern-based model using compression ( 12 ) . Here , we extend this approach to define a generic dissimilarity measure on databases . Moreover , we show that this approach can identify those patterns that characterise the differences between two distributions . Experimental results show that our method provides a well-founded way to independently measure database dissimilarity that allows for thorough inspection of the actual differences . This illustrates the use of our approach in real world data mining .
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