A Fast Interactive Sequential Pattern Mining Algorithm Based on Memory Indexing

The sequential pattern mining algorithm discovers all patterns meeting the user specified minimum support threshold. However, it is very impossibly that user could obtain the satisfactory patterns in just one query. The paper proposes a new interactive sequential pattern mining algorithm based on memory indexing, named MIFSPM, which adopts memory indexing technique, so it scans the sequence database only once to read data sequences into memory. Compact lattice frequent pattern tree (abbreviated as LFP-tree) saves previous results, in which the root node saves two minimum support thresholds. Besides, each node does not store frequent patterns and support information, but also index set mapped table (abbreviated as ISMT), except the root node. Rapidly, ISMT is used to mine new frequent sequential patterns without candidates generation. When to update the structure is decided by comparing the two minimum support thresholds, logistic information contained in the index set mapped table is used to fast mine new frequent sequential patterns without candidates generation. Experiments demonstrate the good performance and scalability of MIFSPM, with various minimum support thresholds. Therefore, MIFSPM can mine frequent sequential patterns efficiently and be better than the other algorithms