We propose a new representation of calendars such that users can specify fuzzy calendar constraints to discover asynchronous periodical association rules embedded in temporal databases. We borrow the fuzzy set theory and use the conjunction operation to construct fuzzy calendar patterns and each fuzzy calendar pattern represents an asynchronous periodical behavior. Moreover, different tune intervals have different weights corresponding to their matching degrees to the specified fuzzy calendar pattern. An efficient algorithm is also proposed to find association rules with the specified fuzzy calendar pattern. Unlike levelwise Apriori-based approaches, our method scans the underlying database at most twice. In the first scan, frequent 2-itemsets with their weighted counts in the specified fuzzy calendar pattern are obtained and then all candidate itemsets are generated from the discovered frequent 2-itemsets. Finally, all frequent itemsets with their weighted counts in the specified fuzzy calendar pattern are discovered in one shot. Asynchronous periodical association rules in the specified fuzzy calendar pattern are then obtained.
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