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
         
        
        
        
        
        
        
            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;
         
        
        
        
            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
         
        
        
            DOI : 
10.1109/WIIAT.2008.60