Abstract
The generation of an isotopic map of the reference region featuring local stable isotopic fingerprints requires the application of data mining methods due to the heterogeneity and complexity of the generated data. In this chapter, we explore new techniques to process isotopic data with the ultimate goal of constructing a map of locally characteristic isotopic fingerprints that help predict the places of origin of particular findings and, thus, supports archaeologists in deriving and testing hypotheses. In particular, we propose a new method for feature selection and apply it to a sample dataset of animal bones from the reference region. This application confirms that a multivariate fingerprint is clearly superior over univariate analysis and that the impact of oxygen on the reliability of the fingerprints is not very prominent. These findings confirm that it is possible to explore cremated human material for provenance analysis. Based on these results, we also propose a new spatial clustering method for detecting spatially consistent areas of homogeneous isotopic fingerprints resulting in an isotopic map of the reference region.
Mrs. Ntoutsi was with Ludwig-Maximilians-Universität when the presented work was done.
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Mauder, M., Ntoutsi, E., Kröger, P., Kriegel, HP. (2017). The Isotopic Fingerprint: New Methods of Data Mining and Similarity Search. In: Grupe, G., Grigat, A., McGlynn, G. (eds) Across the Alps in Prehistory. Springer, Cham. https://doi.org/10.1007/978-3-319-41550-5_5
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DOI: https://doi.org/10.1007/978-3-319-41550-5_5
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