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.