Title :
Closed Multidimensional Sequential Pattern Mining
Author :
Songram, Panida ; Boonjing, Veera ; Intakosum, Sarun
Author_Institution :
Dept. of Math. & Comput. Sci., King Mongkut´´s Inst. of Technol., Bangkok
Abstract :
We propose a new method, called closed multidimensional sequential pattern mining, for mining multidimensional sequential patterns. The new method is an integration of closed sequential pattern mining and closed itemset pattern mining. Based on this method, we show that (1) the number of complete closed multidimensional sequential patterns is not larger than the number of complete multidimensional sequential patterns (2) the set of complete closed multidimensional sequential patterns covers the complete resulting set of multidimensional sequential patterns. In addition, mining using closed itemset pattern mining on multidimensional information would mine only multidimensional information associated with mined closed sequential patterns, and mining using closed sequential pattern mining on sequences would mine only sequences associated with mined closed itemset patterns
Keywords :
data mining; pattern recognition; closed itemset pattern mining; closed multidimensional sequential pattern mining; multidimensional information; Computer science; Data mining; Databases; Itemsets; Laboratories; Mathematics; Multidimensional systems; Printers; Software systems; Systems engineering and theory; closed; data mining.; multidimensional pattern mining; pattern mining;
Conference_Titel :
Information Technology: New Generations, 2006. ITNG 2006. Third International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
0-7695-2497-4
DOI :
10.1109/ITNG.2006.41
