2002/03/27 by Qingguo Zheng, Ke Xu, Zheng, Qingguo +3
Computer Science · Decision Sciences · #Advanced Database Systems and Queries #Artificial Intelligence (cs.AI) #Data Mining Algorithms and Applications #Data Quality and Management #Databases (cs.DB) #FOS: Computer and information sciences #H.2.8 #cs.AI #cs.DB
paper · pdf · doi:10.48550/arxiv.cs/0203028
12 pages, 5 figures
openalex publication_date 2002/03/27 · arxiv created 2003/01/26 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.