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Towards a context model driven german geo-tagging system

Published: 09 November 2007 Publication History

Abstract

In this paper, we present a new approach for recognition and grounding of geographic proper names for German. Named Entity Recognition (NER) in German is more difficult than in English because not only proper names, but all nouns start with capital letters, which results in a large pool of potential ambiguous entities. Our approach makes critical use of a geographic knowledge base that is more detailed (down to the level of streets) and more structured than most knowledge bases used before. We have designed a three-stepmodel (spotting, typing, referencing) that specifies the sources of information that are necessary for geo-tagging and their dependency relationships. Basic aspects of the model were implemented and evaluated in a proof of concept. The model can be applied to other NER tasks by simply substituting the appropriate knowledge base for the one used here and retraining the model.

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  • (2019)Visualization of Location-Referenced Web Textual Information Based on Map MashupsIEEE Access10.1109/ACCESS.2019.29075707(40475-40487)Online publication date: 2019
  • (2014)Digital Libraries Applications: CBIR, Education, Social Networks, eScience/Simulation, and GISSynthesis Lectures on Information Concepts, Retrieval, and Services10.2200/S00565ED1V01Y201401ICR0326:1(1-175)Online publication date: 28-Mar-2014
  • (2012)Mit „Smart Semantics“ mehr aus unstrukturierten Daten machenFokus Technologiemarkt10.1007/978-3-446-43422-6_13(201-224)Online publication date: 2012
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    cover image ACM Conferences
    GIR '07: Proceedings of the 4th ACM workshop on Geographical information retrieval
    November 2007
    104 pages
    ISBN:9781595938282
    DOI:10.1145/1316948
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    Publication History

    Published: 09 November 2007

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    Author Tags

    1. disambiguation
    2. geographic named entity recognition

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    Overall Acceptance Rate 46 of 61 submissions, 75%

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    Cited By

    View all
    • (2019)Visualization of Location-Referenced Web Textual Information Based on Map MashupsIEEE Access10.1109/ACCESS.2019.29075707(40475-40487)Online publication date: 2019
    • (2014)Digital Libraries Applications: CBIR, Education, Social Networks, eScience/Simulation, and GISSynthesis Lectures on Information Concepts, Retrieval, and Services10.2200/S00565ED1V01Y201401ICR0326:1(1-175)Online publication date: 28-Mar-2014
    • (2012)Mit „Smart Semantics“ mehr aus unstrukturierten Daten machenFokus Technologiemarkt10.1007/978-3-446-43422-6_13(201-224)Online publication date: 2012
    • (2011)Geotagging Aided by Topic Detection with WikipediaAdvancing Geoinformation Science for a Changing World10.1007/978-3-642-19789-5_23(461-477)Online publication date: 17-Mar-2011
    • (2010)Geographical classification of documents using evidence from WikipediaProceedings of the 6th Workshop on Geographic Information Retrieval10.1145/1722080.1722096(1-8)Online publication date: 18-Feb-2010
    • (2010)Suggestive Geo-Tagging Assistance for Geo-Collaboration ToolsGeospatial Thinking10.1007/978-3-642-12326-9_8(143-162)Online publication date: 31-Mar-2010
    • (2008)Automatic acquisition of vernacular placesProceedings of the 10th International Conference on Information Integration and Web-based Applications & Services10.1145/1497308.1497437(662-665)Online publication date: 24-Nov-2008
    • (2008)Pocket geocoder — a proposition of GPS-based tagging system for digital photography2008 Conference on Human System Interactions10.1109/HSI.2008.4581495(532-535)Online publication date: May-2008

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