An Efficient Mining Maximal Frequent Traversal Sequences Algorithm Based on Bidirectional Constraint

Mining maximal frequent traversal sequence is a crucial application in Web usage mining, since users´ traversal pattern and motivation are latent in session sequence at some time segment. A Frequent Traversal Sequence Tree structure with Dwell time (FTSD-Tree) is designed. Utilizing FTSD-Tree to store, compress the session database that is constrained by the bidirectional dwell time, and simplify the configuration of dwell time thresholds during mining. A novel algorithm named maximal frequent traversal sequence mining (MFTSM) is presented, which quickly traverses FTSD-Tree and discovers maximal frequent traversal sequence from the session sequences. Experimental results show that MFTSM can significantly improve the execution time efficiency for mining maximal frequent traversal sequence as long as the decision-makers or users give the appropriate constraints. Our performance study at runtime shows that MFTSM is faster than the well-known algorithms GSP, SPAM, MSPS and SPADE in the time constraint environment