Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …

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 …

The connected environment provides real-time information about surrounding traffic; such
information can be helpful in complex driving manoeuvres, such as lane-changing, that …

The monograph Data Clustering: Theory, Algorithms, and Applications was published in
2007. Starting with the common ground and knowledge for data clustering, the monograph …

Many high level representations of time series have been proposed for data mining,
including Fourier transforms, wavelets, eigenwaves, piecewise polynomial models, etc …

The problem of similarity search in large time series databases has attracted much attention
recently. It is a non-trivial problem because of the inherent high dimensionality of the data …

In the last decade there has been an explosion of interest in mining time series data.
Literally hundreds of papers have introduced new algorithms to index, classify, cluster and …

In recent years, there has been an explosion of interest in mining time-series databases. As
with most computer science problems, representation of the data is the key to efficient and …

There has been much recent interest in adapting data mining algorithms to time series
databases. Most of these algorithms need to compare time series. Typically some variation …