A multithreaded hybrid framework for mining frequent itemsets

Efficiently Mining Maximal Frequent Itemsets

We present GenMax, a backtrack search based algorithm for mining maximal frequent itemsets. GenMax uses a number of optimizations to prune the search space. It uses a novel technique called progressive focusing to perform maximality checking, and diffset propagation to perform fast frequency computation. Systematic experimental comparison with previous work indicates that different methods have...

Mining Frequent Itemsets for Protein Kinase Regulation

Efficient Algorithms for Mining Share-frequent Itemsets

Itemset share has been proposed to evaluate the significance of itemsets for mining association rules in databases. The Fast Share Measure (FSM) algorithm is one of the best algorithms to discover all share-frequent itemsets efficiently. However, FSM is fast only when dealing with small datasets. In this study, we shall propose a revised version of FSM, called the Enhanced FSM (EFSM) algorithm ...

Fast Algorithms for Mining Frequent Itemsets

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Frequent Itemsets Mining for Database Auto-Administration

With the wide development of databases in general and data warehouses in particular, it is important to reduce the tasks that a database administrator must perform manually. The aim of auto-administrative systems is to administrate and adapt themselves automatically without loss (or even with a gain) in performance. The idea of using data mining techniques to extract useful knowledge for admini...