title: |
Linguistic Summarization of Time Series Data using Genetic Algorithms |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
| pages: | 416 - 423 | |
DOI: |
To be assigned soon (how to use a DOI) | |
author(s): |
Rita Castillo-Ortega, Nicol¨¢s Mar¨ªn, Daniel S¨¢nchez, Andrea G.B. |
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publication date: |
July 2011 |
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keywords: |
Linguistic Summarization, Multi Objective Evolutionary Algorithms, Time Series, Dimensional Data Model, Fuzzy Logic |
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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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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |