The Maximal Regular Patterns Mining Algorithm Based on Landmark Window over Data Stream

Mining regular pattern is an emerging area. To the best of our knowledge, no method has been proposed to mine the maximal regular patterns about data stream. In this paper, the problem of mining maximal regular patterns based on the landmark window over data stream is focused at the first time. In order to resolve the issue that the nave algorithm which is used to handle the maximal regular patterns mining based on the landmark window over data stream does not have the characteristic of incremental computation, the DSMRM-BLW(data stream maximal regular patterns mining based on boundary landmark window) algorithm is proposed. It takes the first window as the boundary landmark window, and handles it with the nave algorithm. For all other windows, it can obtain the maximal regular patterns over them based on the ones over the adjacent last window incrementally, and can overcome the drawback of the nave algorithm. It is revealed by the extensive experiments that the DSMRM-BLW algorithm is effective in dealing with the maximal regular patterns mining based on the landmark window over data stream, and outperforms the nave algorithm in execution time and space consumption.