In the era of big data, practical applications in various domains continually generate large-
scale time-series data. Among them, some data show significant or potential periodicity …

Mining periodic patterns in time series databases is a daunting research task that plays a
significant role at decision making in real life applications. There are many algorithms for …

Analyzing and mining time-series data by taking advantage of the correlation between the
data values can provide outstanding beneficial. But data owners may be unwilling to publish …

Advances in information technology, together with the evolution of systems in control,
automation and instrumentation have enabled the recovery, storage and manipulation of a …

Periodic pattern mining is a topic for mining periodic event patterns with sufficient
confidence. The resulted patterns are often used to predict future events because they have …

Cycles are fundamental to human health and behavior. Examples include mood cycles,
circadian rhythms, and the menstrual cycle. However, modeling cycles in time series data is …

Rapid technology integration causes a high dimensional time series data accumulation in
multiple domains and applying the classical data mining tools and techniques becomes a …

The recent emergence of body sensor networks (BSNs) has made it easy to continuously
collect and process various health-oriented data related to temporal, spatial and vital sign …

Periodic pattern mining models analyze patterns which occur periodically in a time-series
database, such as sensor readings of smartphones and/or Internet of Things devices. The …

My research work of the current thesis focuses on the detection of single, multiple and all
repeated patterns in sequences. Many algorithms exist for single pattern detection that take …