Mining association rules in temporal databases

Association rules are used to express “interesting” relationships between items of data in a standard enterprise database. In a temporal database, each tuple is given a start and an end time indicating the period during which the information recorded in the tuple is valid. With a temporal database, we may wish to discover relationships between items which satisfy certain timing constraints. Existing algorithms for mining association rules cannot be applied to temporal databases directly. This is because, in the existing algorithms, if an itemset is supported by a tuple, the tuple must contain all the items in the itemset. For temporal databases, an itemset, e.g. {A,B}, is supported as long as all the items in {A,B} are contained in a set of tuples which satisfy certain timing constraint (e.g. the duration of the tuples containing A and B overlap each other). In this paper, an algorithm for mining association rules in temporal databases is described. The algorithm allows (a) the itemsets to contain composite items, and (b) the timing constraint on the tuples to be specified by the users