Applying the maximum utility measure in high utility sequential pattern mining
We introduce a new research work, high utility sequential pattern mining with the maximum utility measure. We propose a projection-based PHUS approach for mining this kind of patterns. An effective upper-bound model is proposed to reduce search space in the mining process. The derived patterns are expected to be more reliable in terms of business. Experimental results show that the PHUS is effective in terms of efficiency and scalability.
high utility sequential pattern mining data mining sequence utility upper bound projection