DocumentCode :
2276286
Title :
Efficient Mining of Event-Oriented Negative Sequential Rules
Author :
Zhao, Yanchang ; Zhang, Huaifeng ; Cao, Longbing ; Zhang, Chengqi ; Bohlscheid, Hans
Author_Institution :
Centre for Quantum Comput. & Intell. Syst., Univ. of Technol., Sydney, NSW
Volume :
1
fYear :
2008
fDate :
9-12 Dec. 2008
Firstpage :
336
Lastpage :
342
Abstract :
Traditional sequential pattern mining deals with positive sequential patterns only, that is, only frequent sequential patterns with the appearance of items are discovered. However, it is often interesting in many applications to find frequent sequential patterns with the nonoccurrence of some items, which are referred to as negative sequential patterns. This paper analyzes three types of negative sequential rules and presents a new technique to find event-oriented negative sequential rules. Its effectiveness and efficiency are shown in our experiments.
Keywords :
data mining; event-oriented negative sequential rule; sequential pattern mining; Association rules; Australia; Data engineering; Data mining; Intelligent agent; Intelligent systems; Itemsets; Knowledge engineering; Quantum computing; Terrorism; Negative sequential patterns; negative sequential rules; sequence mining; sequential patterns;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-0-7695-3496-1
Type :
conf
DOI :
10.1109/WIIAT.2008.60
Filename :
4740469
Link To Document :
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