Linguistic Summarization of Time Series Data using Genetic Algorithms
Rita Castillo-Ortega, Nicolás Marín, Daniel Sánchez, Andrea G.B. Tettamanzi
Available Online August 2011.
- https://doi.org/10.2991/eusflat.2011.145How to use a DOI?
- Linguistic Summarization, Multi Objective Evolutionary Algorithms, Time Series, Dimensional Data Model, Fuzzy Logic
- 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.
- 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 (EUSFLAT-11) PB - Atlantis Press SP - 416 EP - 423 SN - 1951-6851 UR - https://doi.org/10.2991/eusflat.2011.145 DO - https://doi.org/10.2991/eusflat.2011.145 ID - Castillo-Ortega2011/08 ER -