SQUIRE: sequential pattern mining with quantities
Chulyun Kim, Jong-Hwa Lim, R.T. Ng, Kyuseok Shim · 2004
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.