A new method is presented to get insight into univariate time series data. The problem addressed here is how to identify patterns and trends on multiple time scales (days, weeks, ...
We address the problem of capturing and tracking local correlations among time evolving time series. Our approach is based on comparing the local auto-covariance matrices (via the...
Fast retrieval of time series in terms of their contents is important in many application domains. This paper studies database techniques supporting fast searches for time series ...
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
Complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Until recently, studies of...