Research Area

Information and Communication Technologies


Simon Factor


Hodei Irola

Oisin Boydell

Jing Su

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Data Analysys Time Series Clustering

Time Series Clustering (TSC)

Simultaneous Clustering Technology

Time Series Clustering (TSC) from CeADAR provides a general time series data clustering system that allows the user to explore different approaches for clustering single variable time series data. This software system assists the user in determining which clustering approach (algorithm and data representation) is most useful for their objectives by allowing them to browse and inspect the different clustering output of various clustering approaches simultaneously. Moreover, this system defines a general approach applicable on real world data across different industries.
How It Works
TSC overcomes problems of usability, understanding, and comparison by providing an intuitive and easy to use user interface for comparing and analysing the different outputs of a selection of diverse clustering approaches performed over the same input data in a side-by-side comparison. The output of each clustering approach is displayed in a number of different ways such as the raw time series data alongside the normalised data belonging to each cluster and a comparison of the sizes of each cluster. The system can be used to determine which clustering approach is most suitable for a certain objective over a particular dataset.
Presentation and visualisation of multiple time series clustering approaches performed over the same data in a side-by-side way that allows for easy comparison and discovery of which approach is best for different objectives.
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