Back to Search
Start Over
Feature-based Online Segmentation Algorithm for Streaming Time Series (Short Paper)
- Source :
- Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783030129804, CollaborateCom
- Publication Year :
- 2019
- Publisher :
- Springer International Publishing, 2019.
-
Abstract
- Over the last decade, huge number of time series stream data are continuously being produced in diverse fields, including finance, signal processing, industry, astronomy and so on. Since time series data has high-dimensional, real-valued, continuous and other related properties, it is of great importance to do dimensionality reduction as a preliminary step. In this paper, we propose a novel online segmentation algorithm based on the importance of TPs to represent the time series into some continuous subsequences and maintain the corresponding local temporal features of the raw time series data. To demonstrate the advantage of our proposed algorithm, we provide extensive experimental results on different kinds of time series datasets for validating our algorithm and comparing it with other baseline methods of online segmentation.
- Subjects :
- Signal processing
Series (mathematics)
Computer science
Dimensionality reduction
Short paper
02 engineering and technology
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
Feature based
020201 artificial intelligence & image processing
Segmentation
Time series
Baseline (configuration management)
Algorithm
Subjects
Details
- ISBN :
- 978-3-030-12980-4
- ISBNs :
- 9783030129804
- Database :
- OpenAIRE
- Journal :
- Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783030129804, CollaborateCom
- Accession number :
- edsair.doi...........6147f3ece26077e764832d38c53d91ab