A fuzzy approach for mining general temporal association rules in a publication database

In this paper, we handle the problem of mining fuzzy temporal association rules from a publication database, and propose an algorithm to achieve it. In the algorithm, the lifespan of an item is measured by its entire publication periods in a publication database. Also, an itemset table structure is designed to effectively keep and efficiently obtain information of itemsets for mining. Finally, experiments on a simulation dataset were made to show the comparison results of the mined fuzzy frequent itemsets with and without consideration of lifespans of items under different parameter settings.