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- W2143306442 abstract "There is a growing need to analyse sets of complex data, i.e., data in which the individual data items are (semi-) structured collections of data themselves, such as sets of time-series. To perform such analysis, one has to redefine familiar notions such as similarity on such complex data types. One can do that either on the data items directly, or indirectly, based on features or patterns computed from the individual data items. In this paper, we argue that wavelet decomposition is a general tool for the latter approach.KeywordsData ItemComplex DataWavelet DecompositionContinuous Wavelet TransformMultimedia DataThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
- W2143306442 created "2016-06-24" @default.
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- W2143306442 date "2002-01-01" @default.
- W2143306442 modified "2023-10-18" @default.
- W2143306442 title "Complex Data: Mining Using Patterns" @default.
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- W2143306442 doi "https://doi.org/10.1007/3-540-45728-3_3" @default.
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