Mining Surprising Patterns Using Temporal Description Length

We propose a new notion of surprising temporal patterns in market. basket data, and algorithms to find such pat,terns. This is distinct, from finding frequent pat-terns as addressed in the common mining literature. We argue that. once the analyst. is already familiar with prevalent patterns in t,he data, the greatest, increment,al benefit. is likely t,o be from changes in the relationship between item frequencies

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