Abstract
We propose and advocate the use of linguistic summaries as descriptions of trends in time series data. We consider two general types of such summaries: summaries based on frequence and summaries based on duration. We employ the concept of a linguistic database summary due to Yager. To account for a specificity of time series data summarization we employ the Sugeno integrals for linguistic quantifier based aggregation.
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References
[1] I. Batyrshin (2002). On granular Derivatives and the solution of a Granular Initial Value Problem. In International Journal Applied Mathematics and Computer Science, 12(3):403–410.
[2] I. Batyrshin, L. Sheremetov. Perception Based Functions in Qualitative Forecasting. (to appear)
[3] P. Bose, P. L. Lietard, O. Pivert (2003). Sugeno fuzzy integral as a basis for the interpretation of flexible queries involving monotonic aggregates. In Information Processing and Management, 39(2):287–306.
[4] M. Grabisch (1998). Fuzzy integral as a flexible and interpretable tool of aggregation. In Bouchon-Meunier B. (ed.) Aggregation and Fusion of Imperfect Information, Studies in Fuzziness and Soft Computing, Heidelberg, New York: Physica–Verlag, 51–72.
[5] J. Colomer, J. Melendez, J. L. de la Rosa, J. Augilar (1997). A qualitative/quantitative representation of signals for supervision of continuous systems. In Proceedings of the European Control Conference -ECC97, Brussels.
[6] B. Hugeney, B. Bouchon-Meunier (2001). Time-Series Segmentation and Symbolic Representation, from Process-Monitoring to Data- Mining. In LNCS 2206:118–123.
[7] J. Kacprzyk, A. Wilbik, S. Zadroÿzny (2006). Linguistic summarization of trends: an approach. (in press).
[8] J. Kacprzyk and R.R. Yager (2001). Linguistic summaries of data using fuzzy logic. In International Journal of General Systems, 30:33–154.
[9] J. Kacprzyk, R.R. Yager and S. Zadroÿzny (2000). A fuzzy logic based approach to linguistic summaries of databases. InInternational Journal of Applied Mathematics and Computer Science, 10:813–834.
[10] J. Kacprzyk, S. Zadroÿzny (2005). Linguistic database summaries and their protoforms: toward natural language based knowledge discovery tools. In Information Sciences 173:281–304.
[11] J. Kacprzyk, S. Zadroÿzny (2005). Fuzzy linguistic data summaries as a human consistent, user adaptable solution to data mining. In B. Gabrys, K. Leiviska, J. Strackeljan (Eds.) Do Smart Adaptive Systems Exist? Springer, Berlin Heidelberg New York, 321–339.
[12] J. Sklansky and V. Gonzalez (1980) Fast polygonal approximation of digitized curves. In Pattern Recognition 12(5):327–331.
[13] R.R. Yager (1982). A new approach to the summarization of data. In Information Sciences, 28:69–86.
[14] L.A. Zadeh (1983). A computational approach to fuzzy quantiflers in natural languages. In Computers and Mathematics with Applications, 9, 149–184.
[15] L.A. Zadeh (2002). A prototype-centered approach to adding deduction capabilities to search engines — the concept of a protoform. BISC Seminar, University of California, Berkeley.
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Kacprzyk, J., Zadrożny, S., Wilbik, A. (2007). On Linguistic Summaries of Time Series Using a Fuzzy Quantifier Based Aggregation via the Sugeno Integral. In: Castillo, O., Melin, P., Kacprzyk, J., Pedrycz, W. (eds) Hybrid Intelligent Systems. Studies in Fuzziness and Soft Computing, vol 208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37421-3_25
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DOI: https://doi.org/10.1007/978-3-540-37421-3_25
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