When to Update the sequential patterns of stream data?
<|reference_start|>When to Update the sequential patterns of stream data?: In this paper, we first define a difference measure between the old and new sequential patterns of stream data, which is proved to be a distance. Then we propose an experimental method, called TPD (Tradeoff between Performance and Difference), to decide when to update the sequential patterns of stream data by making a tradeoff between the performance of increasingly updating algorithms and the difference of sequential patterns. The experiments for the incremental updating algorithm IUS on two data sets show that generally, as the size of incremental windows grows, the values of the speedup and the values of the difference will decrease and increase respectively. It is also shown experimentally that the incremental ratio determined by the TPD method does not monotonically increase or decrease but changes in a range between 20 and 30 percentage for the IUS algorithm.<|reference_end|>
@article{zheng2002when,
    title={When to Update the sequential patterns of stream data?},
    author={Qingguo Zheng, Ke Xu, Shilong Ma},
    journal={arXiv preprint arXiv:cs/0203028},
    year={2002},
    number={NLSDE_01_2002_3_27},
    archivePrefix={arXiv},
    eprint={cs/0203028},
    primaryClass={cs.DB cs.AI}
}