• DocumentCode
    1791784
  • Title

    Dealing with heterogeneous big data when geoparsing historical corpora

  • Author

    Rupp, C.J. ; Rayson, Paul ; Gregory, Ian ; Hardie, Andrew ; Joulain, Amelia ; Hartmann, Daniel

  • Author_Institution
    Lancaster Univ., Lancaster, UK
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    80
  • Lastpage
    83
  • Abstract
    It has long been known that `variety´ is one of the key challenges and opportunities of big data. This is especially true when we consider the variety of content in historical corpora resulting from large-scale digitisation activities. Collections such as Early English Books Online (EEBO) and the British Library 19th Century Newspapers are extremely large and heterogeneous data sources containing a variety of content in terms of time, location, topic, style and quality. The range of geographical locations referenced in these corpora poses a difficult challenge for state of the art geoparsing tools. In the context of our work on Spatial Humanities analyses, we present our solution for dealing with the variety and scale of these corpora.
  • Keywords
    Big Data; art; libraries; publishing; British Library 19th Century Newspapers; Early English Books Online; art geoparsing tools; geoparsing historical corpora; heterogeneous big data; heterogeneous data sources; large-scale digitisation activities; spatial humanities analyses; Big data; Context; Diseases; Geographic information systems; Geography; Libraries; Pipelines; Historical Corpora; NLP Pipelines and Workflows; Text mining; Toponym Resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (Big Data), 2014 IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/BigData.2014.7004457
  • Filename
    7004457