DiaHClust : an Iterative Hierarchical Clustering Approach for Identifying Stages in Language Change

Schätzle, Christin; Booth, Hannah

DiaHClust : an Iterative Hierarchical Clustering Approach for Identifying Stages in Language Change

Dateien

Schaetzle_2-hopp7ihgb2tj4.pdfGröße: 641.33 KBDownloads: 184

Datum

2019

Open Access-Veröffentlichung

Open Access Bookpart

Sammlungen

Linguistik

Publikationstyp

Beitrag zu einem Konferenzband

Publikationsstatus

Published

Erschienen in

TAHMASEBI, Nina, ed. and others. Proceedings of the 1st International Workshop on Computational Approaches to Historical Language Change. Stroudsburg, PA: Association for Computational Linguistics (ACL), 2019, pp. 126-135. ISBN 978-1-950737-31-4. Available under: doi: 10.18653/v1/W19-4716

Zusammenfassung

Language change is often assessed against a set of pre-determined time periods in order to be able to trace its diachronic trajectory. This is problematic, since a pre-determined periodization might obscure significant developments and lead to false assumptions about the data. Moreover, these time periods can be based on factors which are either arbitrary or non-linguistic, e.g., dividing the corpus data into equidistant stages or taking into account language-external events. Addressing this problem, in this paper we present a data-driven approach to periodization: ‘DiaHClust’. DiaHClust is based on iterative hierarchical clustering and offers a multi-layered perspective on change from text-level to broader time periods. We demonstrate the usefulness of DiaHClust via a case study investigating syntactic change in Icelandic, modelling the syntactic system of the language in terms of vectors of syntactic change.

Fachgebiet (DDC)

400 Sprachwissenschaft, Linguistik

Konferenz

The 1st International Workshop on Computational Approaches to Historical Language Change, 2. Aug. 2019, Florence, Italy

Zitieren

ISO 690

SCHÄTZLE, Christin, Hannah BOOTH, 2019. DiaHClust : an Iterative Hierarchical Clustering Approach for Identifying Stages in Language Change. The 1st International Workshop on Computational Approaches to Historical Language Change. Florence, Italy, 2. Aug. 2019. In: TAHMASEBI, Nina, ed. and others. Proceedings of the 1st International Workshop on Computational Approaches to Historical Language Change. Stroudsburg, PA: Association for Computational Linguistics (ACL), 2019, pp. 126-135. ISBN 978-1-950737-31-4. Available under: doi: 10.18653/v1/W19-4716

BibTex

@inproceedings{Schatzle2019DiaHC-50779,
  year={2019},
  doi={10.18653/v1/W19-4716},
  title={DiaHClust : an Iterative Hierarchical Clustering Approach for Identifying Stages in Language Change},
  isbn={978-1-950737-31-4},
  publisher={Association for Computational Linguistics (ACL)},
  address={Stroudsburg, PA},
  booktitle={Proceedings of the 1st International Workshop on Computational Approaches to Historical Language Change},
  pages={126--135},
  editor={Tahmasebi, Nina},
  author={Schätzle, Christin and Booth, Hannah}
}

RDF

<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/50779">
    <dc:contributor>Booth, Hannah</dc:contributor>
    <dcterms:issued>2019</dcterms:issued>
    <dc:creator>Schätzle, Christin</dc:creator>
    <dcterms:title>DiaHClust : an Iterative Hierarchical Clustering Approach for Identifying Stages in Language Change</dcterms:title>
    <dcterms:abstract xml:lang="eng">Language change is often assessed against a set of pre-determined time periods in order to be able to trace its diachronic trajectory. This is problematic, since a pre-determined periodization might obscure significant developments and lead to false assumptions about the data. Moreover, these time periods can be based on factors which are either arbitrary or non-linguistic, e.g., dividing the corpus data into equidistant stages or taking into account language-external events. Addressing this problem, in this paper we present a data-driven approach to periodization: ‘DiaHClust’. DiaHClust is based on iterative hierarchical clustering and offers a multi-layered perspective on change from text-level to broader time periods. We demonstrate the usefulness of DiaHClust via a case study investigating syntactic change in Icelandic, modelling the syntactic system of the language in terms of vectors of syntactic change.</dcterms:abstract>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/45"/>
    <dc:creator>Booth, Hannah</dc:creator>
    <dc:contributor>Schätzle, Christin</dc:contributor>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/50779"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/45"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/50779/1/Schaetzle_2-hopp7ihgb2tj4.pdf"/>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/50779/1/Schaetzle_2-hopp7ihgb2tj4.pdf"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2020-09-10T12:52:58Z</dc:date>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2020-09-10T12:52:58Z</dcterms:available>
    <dc:rights>Attribution 4.0 International</dc:rights>
    <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by/4.0/"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:language>eng</dc:language>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
  </rdf:Description>
</rdf:RDF>

Universitätsbibliographie

Ja