Mining segment-wise periodic patterns in time-related databases 论文

1998引用 226
Data Mining Algorithms and ApplicationsData Management and AlgorithmsTime Series Analysis and Forecasting

摘要

Periodicity search, that is, search for cyclicity in time-related databases, is an interesting data mining problem. Most previous studies have been on finding full-cycle periodicity for all the segments in the selected sequences of the data, that is, if a sequence is periodic, all the points or segments in the period repeat. However, it is often useful to mine segment-wise or point-wise periodicity in time-related data sets. In this study, we integrate data cube and Apriori data mining techniques for mining segment-wise periodicity in regard to a fixed length period and show that data cube provides an efficient structure and a convenient way for interactive mining of multiple-level periodicity. Introduction Periodicity search, that is, search for cyclic patterns in time-related data sets, is an important data mining problem with many applications. Most previously studied methods on periodicity pattern search are on mining full-cycle periodicity in the sense that every point in the pe...