Linguistic Summarization of Time Series Data using Genetic Algorithms

DOI

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.

Copyright

© 2011, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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 (EUSFLAT-11)
PB  - Atlantis Press
SP  - 416
EP  - 423
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2011.145
DO  - 10.2991/eusflat.2011.145
ID  - Castillo-Ortega2011/08
ER  -