Title
A Global Constraint For Closed Frequent Pattern Mining
Abstract
Discovering the set of closed frequent patterns is one of the fundamental problems in Data Mining. Recent Constraint Programming (CP) approaches for declarative itemset mining have proven their usefulness and flexibility. But the wide use of reified constraints in current CP approaches leads to difficulties in coping with high dimensional datasets. In this paper, we propose the CLOSEDPATTERN global constraint to capture the closed frequent pattern mining problem without requiring reified constraints or extra variables. We present an algorithm to enforce domain consistency on CLOSEDPATTERN in polynomial time. The computational properties of this algorithm are analyzed and its practical effectiveness is experimentally evaluated.
Year
DOI
Venue
2016
10.1007/978-3-319-44953-1_22
PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING, CP 2016
Field
DocType
Volume
Mathematical optimization,Computer science,Constraint programming,Constraint satisfaction problem,Time complexity
Conference
9892
ISSN
Citations 
PageRank 
0302-9743
2
0.38
References 
Authors
11
7
Name
Order
Citations
PageRank
Nadjib Lazaar13612.25
Yahia Lebbah211519.34
Samir Loudni315221.48
mehdi maamar431.40
Valentin Lemière520.38
Christian Bessière61520114.38
Patrice Boizumault729431.56