Optimized Sequential Pattern Mining from Point Of Sales Data

We consider an optimization problem of sequential pattern mining. We present space efficient algorithms for computing optimized sequential pattern that maximize transitive confidence from a cause event to an effect event. Those can compute optimized sequential patterns for all cause-effect pairs of sales fluctuation events in large POS data.