In this article we describe a very new kind of subspace representation for time series which is particularly suited to preserve essential trend information ...
Subspace representations that preserve essential information of high-dimensional data may be advantageous for many reasons such as improved interpretability ...
Oct 22, 2024 · In this article, we investigate the properties of the polynomial shape space representation and the shape space distance measure by means of ...
Abstract Shapes are a concise way to describe temporal variable behaviors. Some commonly used shapes are spikes, sinks, rises, and drops.
Journal article. Temporal data mining using shape space representations of time series. Publication Details. Authors: Fuchs, E.; Gruber, T.; Pree, H.; Sick, ...
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Temporal data mining deals with the harvesting of useful information from temporal data. New initiatives in health care and business organizations have ...
This way, each time series is converted into a binary sequence, perfectly suited to be manipulated by genetic algorithms [63]. A different approach to convert a ...
ABSTRACT. Very large time series are increasingly available from an ever wider range of IoT-enabled sensors deployed in different environments.
Temporal data mining using shape space representations of time series. E. Fuchs, T. Gruber, H. Pree, und B. Sick. Neurocomputing, 74 (1-3): 379-393 (2010 ). 3.
Temporal data in general and times series in particular are ubiquitous in our current world. They are recorded from various sensors in many application domains ...