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.
Linguistic summarization of time series data using genetic algorithms / R. Castillo-Ortega, N. Marín, D. Sánchez, A.G.B. Tettamanzi - In: Proceedings of EUSFLAT-LFA 2011, European Society for fuzzy logic and technology : 18-22 july 2011, Aix-les-Bains, France / [a cura di] S. Galichet, J. Montero, G. Mauris. - Amsterdam : Atlantis Press, 2011. - ISBN 9789078677000. - pp. 416-423 (( Intervento presentato al 7. convegno EUSFLAT tenutosi a Aix-Les-Bains nel 2011 [10.2991/eusflat.2011.145].
Linguistic summarization of time series data using genetic algorithms
A.G.B. TettamanziUltimo
2011
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.File | Dimensione | Formato | |
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