An Enhanced Method to Mine Rare Item Sets using Multiple Item Sets Support based on CP-Tree

A Novel Approach to Mine Frequent Item sets of Process

Item Sets that Compress

One of the major problems in frequent item set mining is the explosion of the number of results: it is difficult to find the most interesting frequent item sets. The cause of this explosion is that large sets of frequent item sets describe essentially the same set of transactions. In this paper we approach this problem using the MDL principle: the best set of frequent item sets is that set that...

Mining Fuzzy Frequent Item Sets

Due to various reasons transaction data often lack information about some items. This leads to the problem that some potentially interesting frequent item sets cannot be discovered, since by exact matching the number of supporting transactions may be smaller than the user-specified minimum. In this study we try to find such frequent item sets nevertheless by inserting missing items into transac...

Discovering Relational Item Sets Efficiently

Frequent item set mining is a major data mining research area. Generalising from the standard single table case to a multirelational setting is simple in principle, but hard in practice. That is, it is simple to define frequent item sets in the multirelational setting, as well as extending the A-Priori algorithm. It is hard, because the well-known frequent pattern explosion at low min-sup setti...

A Tree Projection Algorithm for Generation of Frequent Item Sets

In this paper we propose algorithms for generation of frequent itemsets by successive construction of the nodes of a lexicographic tree of itemsets. We discuss di erent strategies in generation and traversal of the lexicographic tree such as breadthrst search, depthrst search or a combination of the two. These techniques provide di erent trade-o s in terms of the I/O, memory and computational t...