 The candidate generation in a usual Apriori style would give (A, B, C) as a 3-itemset, but in the present context we get the following 3-sequences as a result of joining the above 2- sequences
The candidate–generation phase takes this into account.The GSP algorithm discovers frequent sequences, allowing for time constraints such as maximum gap and minimum gap among the sequence elements.Moreover, it supports the notion of a sliding window, i.e., of a time interval within which items are observed as belonging to the same event, even if they originate from different events.