In almost every scientific field, measurements are performed over time. These observations
lead to a collection of organized data called time series. The purpose of time-series data …

Time series is an important class of temporal data objects and it can be easily obtained from
scientific and financial applications. A time series is a collection of observations made …

Given a financial time series such as, or any historical data in stock markets, how can we
obtain useful information from recent transaction data to predict the ups and downs at the …

Subsequence anomaly detection in long sequences is an important problem with
applications in a wide range of domains. However, the approaches proposed so far in the …

Time series analysis is a key technique for extracting and predicting events in domains as
diverse as epidemiology, genomics, neuroscience, environmental sciences, economics, and …

Recognition of motions and activities of objects in videos requires effective representations
for analysis and matching of motion trajectories. In this paper, we introduce a new …

Last decades witness a huge growth in medical applications, genetic analysis, and in
performance of manufacturing technologies and automatised production systems. A …

Subsequence anomaly (or outlier) detection in long sequences is an important problem with
applications in a wide range of domains. However, the approaches that have been …

The detection of repeated subsequences, time series motifs, is a problem which has been
shown to have great utility for several higher-level data mining algorithms, including …

In the last 15 years, data series motif and discord discovery have emerged as two useful and
well-used primitives for data series mining, with applications to many domains, including …