Huge time-series stream data are collected every day from many areas, and their trends may be impacted by outside events, hence biased from its normal behavior. This phenomenon is ...
Yue Wang, Jie Zuo, Ning Yang, Lei Duan, Hong-Jun L...
Many decision support systems, which utilize association rules for discovering interesting patterns, require the discovery of association rules that vary over time. Such rules des...
Sridhar Ramaswamy, Sameer Mahajan, Abraham Silbers...
The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical ...
Abstract. A method is proposed to determine the similarity of a collection of time series. As a first step, one extracts events from the time series, in other words, one converts e...
Most time series data mining algorithms use similarity search as a core subroutine, and thus the time taken for similarity search is the bottleneck for virtually all time series d...
Thanawin Rakthanmanon, Bilson J. L. Campana, Abdul...