The problem of finding association rules from a dataset is to find all possible associations that hold among the items, given a minimum support value and a minimum confidence. This involves finding frequent sets first and then the association rules that hold within the items in the frequent sets. The problem of mining temporal association rules from temporal dataset is to find association rules...

Exception rules have been previously defined as rules with low interest and high confidence. In this paper a new approach to mine exception rules will be proposed and evaluated. Interconnection between exception and negative association rules will be considered. Based on the knowledge about negative association rules in the database, the candidate exception rules will be generated. A novel exce...

Association rule mining is an important branch of data mining research that aims to extract important relations from data. In this paper, we develop a new framework for mining association rules based on minimal predictive rules (MPR). Our objective is to minimize the number of rules in order to reduce the information overhead, while preserving and concisely describing the important underlying p...

Now a day’s companies have large amount of data its exploration becomes complicated, especially if we emphasize the temporal aspect while considering association rules. Therefore, we are introducing the temporal association rules mining. In this paper, we focus on cyclic association rules, classified as a category of the temporal association rules. An association rule is cyclic if the rule has ...