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Identifying destinations automatically from human generated route directions

Published: 01 November 2011 Publication History

Abstract

Automatic and accurate extraction of destinations in human-generated route descriptions facilitates visualizing text route descriptions on digital maps. Such information further supports research aiming at understanding human cognition of geospatial information. However, as reproted in previous work, the recognition of destinations is not satisfactory. In this paper, we show our approach and achievements in improving the accuracy of destination name recognition. We identified and evaluated multiple features for classifying a named entity to be either "destination" or "non-destination"; after that, we use a simple yet effective post-processing algorithm to improve classification accuracy. Comprehensive experiments confirm the effectiveness of our approach.

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Cited By

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  • (2018)Leveraging tuberculosis case relative locations to enhance case detection and linkage to care in SwazilandGlobal Health Research and Policy10.1186/s41256-018-0058-y3:1Online publication date: 5-Feb-2018
  • (2014)Computational Aspects: How Landmarks Can Be Observed, Stored, and AnalysedLandmarks10.1007/978-3-319-05732-3_5(137-173)Online publication date: 3-Apr-2014

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  1. Identifying destinations automatically from human generated route directions

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    cover image ACM Conferences
    GIS '11: Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
    November 2011
    559 pages
    ISBN:9781450310314
    DOI:10.1145/2093973

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 01 November 2011

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    Author Tags

    1. destination name classification
    2. driving directions
    3. geospatial information extraction

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    • (2018)Leveraging tuberculosis case relative locations to enhance case detection and linkage to care in SwazilandGlobal Health Research and Policy10.1186/s41256-018-0058-y3:1Online publication date: 5-Feb-2018
    • (2014)Computational Aspects: How Landmarks Can Be Observed, Stored, and AnalysedLandmarks10.1007/978-3-319-05732-3_5(137-173)Online publication date: 3-Apr-2014

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