Mining traditional association rules using frequent itemsets lattice

There are many methods which have been developed for improvement of time in mining frequent itemsets. However, the methods which deal with the time of mining association rules were not put in deep research. In reality, in case of database which contains many frequent itemsets (from ten thousands up to millions), the time of mining association rules is much larger than that needed for mining frequent itemsets. In this paper, we present an application of lattice in mining traditional association rules which will reduce greatly the time for mining rules - our method includes two phases: (1) building frequent itemsets lattice and (2) mining association rules from lattice. We based on the parent-child relationships in lattice to fast discover the association rules. The experiments show that the mining rules from lattice is more effective than the direct mining from frequent itemsets using hash table.

[1]  Mohammed J. Zaki,et al.  Fast vertical mining using diffsets , 2003, KDD '03.

[2]  Vicky Choi.  Faster Algorithms for Constructing a Concept (Galois) Lattice , 2006, ArXiv.

[3]  Sergei O. Kuznetsov,et al.  Comparing performance of algorithms for generating concept lattices , 2002, J. Exp. Theor. Artif. Intell..

[4]  Gösta Grahne,et al.  Efficiently Using Prefix-trees in Mining Frequent Itemsets , 2003, FIMI.

[5]  Gerd Stumme,et al.  Mining Minimal Non-redundant Association Rules Using Frequent Closed Itemsets , 2000, Computational Logic.

[6]  Jiuyong Li.  On optimal rule discovery , 2006 .

[7]  Mohammed J. Zaki,et al.  Efficient algorithms for mining closed itemsets and their lattice structure , 2005, IEEE Transactions on Knowledge and Data Engineering.

[8]  Kenneth McGarry,et al.  A survey of interestingness measures for knowledge discovery , 2005, The Knowledge Engineering Review.

[9]  Yiyu Yao,et al.  A Measurement-Theoretic Foundation of Rule Interestingness Evaluation , 2006, Foundations and Novel Approaches in Data Mining.

[10]  Tomasz Imielinski,et al.  Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.

[11]  Mohammed J. Zaki.  Mining Non-Redundant Association Rules , 2004, Data Min. Knowl. Discov..

[12]  Rakesh Agarwal,et al.  Fast Algorithms for Mining Association Rules , 1994, VLDB 1994.

[13]  Jiawei Han,et al.  Data Mining: Concepts and Techniques, Second Edition , 2006, The Morgan Kaufmann series in data management systems.

[14]  Jian Pei,et al.  CLOSET+: searching for the best strategies for mining frequent closed itemsets , 2003, KDD '03.

[15]  Ramakrishnan Srikant,et al.  Fast algorithms for mining association rules , 1998, VLDB 1998.

[16]  Roberto J. Bayardo,et al.  Mining the most interesting rules , 1999, KDD '99.

[17]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[18]  G. Grahne,et al.  High Performance Mining of Maximal Frequent Itemsets Gösta , 2003 .