I am working with sequence data which are long lists of malware win-api calls. I am trying to cast the problem of identifying 'malware behavior' into one of finding sequential patterns. I treat each api call as a single item Itemset. The number of different possible items (api calls) is quite large.
Now, when I apply the SPADE algorithm (see also, Zaki, SPADE: An Efficient Algorithm for Mining Frequent Sequences, Machine Learning, 42, 31–60, 2001) I run into memory problems. Is there a better alternative way to find sequential patterns among large high vocabulary sequences?