TY - JOUR
T1 - Constraint-based sequential pattern mining
T2 - The pattern-growth methods
AU - Pei, Jian
AU - Han, Jiawei
AU - Wang, Wei
N1 - Funding Information:
This research is supported in part by NSF Grant IIS-0308001, a President’s Research Grant, an Endowed Research Fellowship Award and a startup grant in Simon Fraser University. All opinions, findings, conclusions and recommendations in this paper are those of the authors and do not necessarily reflect the views of the funding agencies.
Funding Information:
This research is supported in part by NSERC Grant 312194-05, NSF Grants IIS-0308001, IIS-0513678, BDI-0515813 and National Science Foundation of China (NSFC) grants No. 60303008 and 69933010. All opinions, findings, conclusions and recommendations in this paper are those of the authors and do not necessarily reflect the views of the funding agencies.
PY - 2007/4
Y1 - 2007/4
N2 - Constraints are essential for many sequential pattern mining applications. However, there is no systematic study on constraint-based sequential pattern mining. In this paper, we investigate this issue and point out that the framework developed for constrained frequent-pattern mining does not fit our mission well. An extended framework is developed based on a sequential pattern growth methodology. Our study shows that constraints can be effectively and efficiently pushed deep into the sequential pattern mining under this new framework. Moreover, this framework can be extended to constraint-based structured pattern mining as well.
AB - Constraints are essential for many sequential pattern mining applications. However, there is no systematic study on constraint-based sequential pattern mining. In this paper, we investigate this issue and point out that the framework developed for constrained frequent-pattern mining does not fit our mission well. An extended framework is developed based on a sequential pattern growth methodology. Our study shows that constraints can be effectively and efficiently pushed deep into the sequential pattern mining under this new framework. Moreover, this framework can be extended to constraint-based structured pattern mining as well.
KW - Frequent pattern mining
KW - Mining with constraints
KW - Pattern-growth methods
KW - Sequential pattern mining
UR - http://www.scopus.com/inward/record.url?scp=33947584673&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33947584673&partnerID=8YFLogxK
U2 - 10.1007/s10844-006-0006-z
DO - 10.1007/s10844-006-0006-z
M3 - Article
AN - SCOPUS:33947584673
SN - 0925-9902
VL - 28
SP - 133
EP - 160
JO - Journal of Intelligent Information Systems
JF - Journal of Intelligent Information Systems
IS - 2
ER -