Combination of dynamic bit vectors and transaction information for mining frequent closed sequences efficiently

Sequence mining algorithms attempt to mine all possible frequent sequences. These algorithms produce redundant results, increasing the required storage space and runtime, especially for large sequence databases. In recent years, many studies have proved that mining frequent closed sequences is more efficient than mining all frequent sequences. The desired information can be fully extracted from frequent closed sequences. Most algorithms for mining frequent closed sequences use a candidate maintenance-and-test paradigm. The present paper proposes an algorithm called CloFS-DBV that uses dynamic bit vectors. Various methods are employed to reduce memory usage and runtime. Experimental results show that CloFS-DBV is more efficient than the BIDE and CloSpan algorithms in terms of execution time and memory usage.