Data Mining and Knowledge Discovery

, Volume 11, Issue 3, pp 223–242

GenMax: An Efficient Algorithm for Mining Maximal Frequent Itemsets

Original Article

DOI: 10.1007/s10618-005-0002-x

Cite this article as:
Gouda, K. & Zaki, M.J. Data Min Knowl Disc (2005) 11: 223. doi:10.1007/s10618-005-0002-x


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 varying strengths and weaknesses based on dataset characteristics. We found GenMax to be a highly efficient method to mine the exact set of maximal patterns.


maximal itemsetsfrequent itemsetsassociation rulesdata miningbacktracking search

Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  1. 1.Department of MathematicsFaculty of ScienceBenhaEgypt
  2. 2.Computer Science DepartmentRensselaer Polytechnic InstituteTroyUSA