BFSPMiner is an effective and efficient batch-free algorithm for mining sequential patterns over data streams was published very recently https://link.springer.com/article/10.1007/s41060-017-0084-8. An implementation of the algorithm is available here: https://github.com/Xsea/BFSPMiner. As BFSPMiner has proven to be effective (see Figures 10-14 of the paper) in different domains (see Table 1 in the paper), we would like to use it for detecting drifts in the underlying stream. This can be done, for instance, by observing considerable statistical deviations in the discovered top k patterns. Additionally, for more adaptation to the streaming settings, a new method is needed to adaptively change the optimal value of the maximal pattern length.
Contact: Dr. ing. Marwan Hassani.