Abstract
In order to analyze the quality of web data harvest, it is important to consider the variability of the volumes of data harvested over time. However, these volumes of data collected over time form more trend information than accurate information due to the non-exhaustiveness of the harvests and the temporal evolution of the strategies. They form imprecise time series data. Therefore, due to the characteristics of the data, the variability of a particular series must be considered in relation to the other series. The purpose of this paper is to propose a fuzzy approach to measure the variability of time series of imprecise data represented by intervals. Our approach is based (1) on the construction of fuzzy clusters on all data at each time-stamp (2) on the difference in the positioning of data in clusters at each time-stamp.
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Othmane, Z.B., de Runz, C., Younes, A.A., Mercelot, V. (2019). Quantify the Variability of Time Series of Imprecise Data. In: Cuzzocrea, A., Greco, S., Larsen, H., Saccà, D., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2019. Lecture Notes in Computer Science(), vol 11529. Springer, Cham. https://doi.org/10.1007/978-3-030-27629-4_20
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