A Novel Approach for finding Frequent Item Sets with Hybrid Strategies

A Novel Approach for finding Frequent Item Sets with Hybrid Strategies

Frequent item sets mining plays an important role in association rules mining. Over the years, a variety of algorithms for finding frequent item sets in very large transaction databases have been developed. Therefore, a number of methods have been proposed recently to discover approximate frequent item sets. This paper proposes an efficient SMine (Sorted Mine) Algorithm for finding frequent ite...

A Novel Approach to Mine Frequent Item sets of Process

New algorithms for finding approximate frequent item sets

In standard frequent item set mining a transaction supports an item set only if all items in the set are present. However, in many cases this is too strict a requirement that can render it impossible to find certain relevant groups of items. By relaxing the support definition, allowing for some items of a given set to be missing from a transaction, this drawback can be amended. The resulting it...

Finding Frequent Subgraphs in Biological Networks Via Maximal Item Sets

Mining Frequent Item Sets with Convertible Constraints

Recent work has highlighted the importance of the constraint-based mining paradigm in the context of frequent itemsets, associations, correlations, sequential patterns, and many other interesting patterns in large databases. In this paper, we study constraints which cannot be handled with existing theory and techniques. For example, , , ( can contain items of arbitrary values) "!$# %'&)( , are ...