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            Chapter Towards automated language classification

            A clustering approach

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            Author(s)
            Buch, Armin
            Erschler, David
            Jäger, Gerhard
            Lupas, Andrei
            Contributor(s)
            Saxena, Anju (editor)
            Borin, Lars (editor)
            Collection
            European Research Council (ERC)
            Language
            English
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            Abstract
            In this paper, we discuss advantages of clustering approaches to automated language classification, describe distance measures used for this purpose, and present results of several proof-of-concept experiments. We advocate the use of probability based distances – those that take into account the distribution of relevant features across the language sample in question
            Book
            Approaches to Measuring Linguistic Differences; Approaches to Measuring Linguistic Differences; Approaches to Measuring Linguistic Differences
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/168281
            Keywords
            linguistic differences; thema EDItEUR::C Language and Linguistics::CF Linguistics
            DOI
            10.1515/9783110305258.303
            ISBN
            9783110488081
            Publisher
            De Gruyter
            Publisher website
            http://www.degruyter.com/
            Publication date and place
            Berlin/Boston, 2013
            Grantor
            • FP7 Ideas: European Research Council
            • OAPEN harvesting collection

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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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