Pushing Convertible Constraints in Frequent Itemset Mining

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. Constraint pushing techniques have been developed for mining frequent patterns and associations with antimonotonic, monotonic, and succinct constraints. In this paper, we study constraints which cannot be handled with existing theory and techniques in frequent pattern mining. For example, avg(S)θv, median(S)θv, sum(S)θv (S can contain items of arbitrary values, θ ∈ {<, <, ≤, ≥} and v is a real number.) are customarily regarded as “tough” constraints in that they cannot be pushed inside an algorithm such as Apriori. We develop a notion of convertible constraints and systematically analyze, classify, and characterize this class. We also develop techniques which enable them to be readily pushed deep inside the recently developed FP-growth algorithm for frequent itemset mining. Results from our detailed experiments show the effectiveness of the techniques developed.

[1]  Dimitrios Gunopulos,et al.  Constraint-Based Rule Mining in Large, Dense Databases , 2004, Data Mining and Knowledge Discovery.

[2]  Jian Pei,et al.  Mining frequent patterns without candidate generation , 2000, SIGMOD 2000.

[3]  Laks V. S. Lakshmanan,et al.  Exploratory mining and pruning optimizations of constrained associations rules , 1998, SIGMOD '98.

[4]  Jinyan Li,et al.  Efficient mining of emerging patterns: discovering trends and differences , 1999, KDD '99.

[5]  Jennifer Widom,et al.  Clustering association rules , 1997, Proceedings 13th International Conference on Data Engineering.

[6]  Jian Pei,et al.  Can we push more constraints into frequent pattern mining? , 2000, KDD '00.

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

[8]  A. Akhmetova.  Discovery of Frequent Episodes in Event Sequences , 2006 .

[9]  Dimitrios Gunopulos,et al.  Constraint-Based Rule Mining in Large, Dense Databases , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).

[10]  Heikki Mannila,et al.  Efficient Algorithms for Discovering Association Rules , 1994, KDD Workshop.

[11]  Kyuseok Shim,et al.  SPIRIT: Sequential Pattern Mining with Regular Expression Constraints , 1999, VLDB.

[12]  Jian Pei,et al.  Mining frequent patterns without candidate generation , 2000, SIGMOD '00.

[13]  Jian Pei,et al.  CLOSET: An Efficient Algorithm for Mining Frequent Closed Itemsets , 2000, ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery.

[14]  Ramakrishnan Srikant,et al.  Mining Association Rules with Item Constraints , 1997, KDD.

[15]  Roberto J. Bayardo,et al.  Efficiently mining long patterns from databases , 1998, SIGMOD '98.

[16]  Rajeev Motwani,et al.  Beyond market baskets: generalizing association rules to correlations , 1997, SIGMOD '97.

[17]  Geoffrey I. Webb.  OPUS: An Efficient Admissible Algorithm for Unordered Search , 1995, J. Artif. Intell. Res..

[18]  Rajeev Motwani,et al.  Scalable Techniques for Mining Causal Structures , 1998, Data Mining and Knowledge Discovery.

[19]  Ron Rymon,et al.  Search through Systematic Set Enumeration , 1992, KR.

[20]  Laks V. S. Lakshmanan,et al.  Optimization of constrained frequent set queries with 2-variable constraints , 1999, SIGMOD '99.

[21]  Laks V. S. Lakshmanan,et al.  Efficient mining of constrained correlated sets , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).

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

[23]  Heikki Mannila,et al.  Finding interesting rules from large sets of discovered association rules , 1994, CIKM '94.

[24]  Ramakrishnan Srikant,et al.  Mining sequential patterns , 1995, Proceedings of the Eleventh International Conference on Data Engineering.

[25]  Jiawei Han,et al.  Efficient mining of partial periodic patterns in time series database , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).

[26]  Ramakrishnan Srikant,et al.  Fast Algorithms for Mining Association Rules in Large Databases , 1994, VLDB.

[27]  Laks V. S. Lakshmanan,et al.  Mining frequent itemsets with convertible constraints , 2001, Proceedings 17th International Conference on Data Engineering.