EXTRACTING PATTERNS FROM SEQUENTIAL DATA

Described is a technology in which sequential data, such as application program command sequences, are processed into patterns, such as for use in analyzing program usage. In one aspect, sequential data may be first transformed via state machines that remove repeated data, group similar data into sub-sequences, and/or remove noisy data. The transformed data is then segmented into units. A pattern extraction mechanism extracts patterns from the units into a pattern set, by calculating a stability score (e.g., a mutual information score) between succeeding units, selecting the pair of units having the most stability (e.g., the highest score), and adding corresponding information for that pair into the pattern set. Pattern extraction is iteratively repeated until a stopping criterion is met, e.g., the pattern set reaches a defined size, or when the stability score is smaller than a pre-set threshold.