A weight-order-based lattice algorithm for mining maximal weighted frequent patterns over a data stream sliding window

The weighted maximal frequent pattern concerning both the importance and the count is the pattern which is not the subset of any other pattern and the weighted support is large enough. To mine such a pattern based on the sliding window model, the WMFP-SW algorithm was proposed. However, when the new transaction comes, it always has to reconstruct its FP-tree. To solve the problem, we propose the WOB Lattice algorithm and our algorithm provides better performance than the WMFP-SW algorithm.