Frequent itemsets mining is a popular framework for pattern discovery. In this framework, given a database of customer transactions, the task is to unearth all patterns in the for...
Srivatsan Laxman, Prasad Naldurg, Raja Sripada, Ra...
The rapid growth of transactional data brought, soon enough, into attention the need of its further exploitation. In this paper, we investigate the problem of securing sensitive k...
Traditional methods for frequent itemset mining typically assume that data is centralized and static. Such methods impose excessive communication overhead when data is distributed...
Matthew Eric Otey, Chao Wang, Srinivasan Parthasar...
A simple new algorithm is suggested for frequent itemset mining, using item probabilities as the basis for generating candidates. The method first finds all the frequent items, an...
This paper explores the generation of candidates, which is an important step in frequent itemset mining algorithms, from a theoretical point of view. Important notions in our prob...