Title :
SQUIRE: sequential pattern mining with quantities
Author :
Kim, Chulyun ; Lim, Jong-Hwa ; Ng, Raymond ; Shim, Kyuseok
Author_Institution :
Seoul Nat. Univ., South Korea
fDate :
30 March-2 April 2004
Abstract :
In this paper, we consider the problem of mining sequential patterns with quantities. Naive extensions to existing algorithms for sequential patterns are inefficient, as they may enumerate the search space blindly. To alleviate the situation, we propose hash filtering and quantity sampling techniques that significantly improve the performance of the naive extensions.
Keywords :
data mining; pattern recognition; sampling methods; SQUIRE; hash filtering; naive extensions; quantity sampling techniques; search space; sequential pattern mining; Data engineering; Data mining; Databases; Filtering; Itemsets; Pattern analysis; Performance analysis; Sampling methods; Writing;
Conference_Titel :
Data Engineering, 2004. Proceedings. 20th International Conference on
Print_ISBN :
0-7695-2065-0
DOI :
10.1109/ICDE.2004.1320058