Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-11)

Linguistic Summarization of Time Series Data using Genetic Algorithms

Authors
Rita Castillo-Ortega, Nicolás Marín, Daniel Sánchez, Andrea G.B. Tettamanzi
Corresponding Author
Rita Castillo-Ortega
Available Online August 2011.
DOI
https://doi.org/10.2991/eusflat.2011.145How to use a DOI?
Keywords
Linguistic Summarization, Multi Objective Evolutionary Algorithms, Time Series, Dimensional Data Model, Fuzzy Logic
Abstract
In this paper, the use of an evolutionary approach when obtaining linguistic summaries from time series data is proposed. We assume the availability of a hierarchical partition of the time dimension in the time series. The use of natural language allows the human users to understand the resulting summaries in an easy way. The number of possible final summaries and the different ways of measuring their quality has taken us to adopt the use of a multi objective evolutionary algorithm. We compare the results of the new approach with our previous greedy algorithms.
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Proceedings
Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology
Part of series
Advances in Intelligent Systems Research
Publication Date
August 2011
ISBN
978-90-78677-00-0
DOI
https://doi.org/10.2991/eusflat.2011.145How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Rita Castillo-Ortega
AU  - Nicolás Marín
AU  - Daniel Sánchez
AU  - Andrea G.B. Tettamanzi
PY  - 2011/08
DA  - 2011/08
TI  - Linguistic Summarization of Time Series Data using Genetic Algorithms
BT  - Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 416
EP  - 423
UR  - https://doi.org/10.2991/eusflat.2011.145
DO  - https://doi.org/10.2991/eusflat.2011.145
ID  - Castillo-Ortega2011/08
ER  -