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  • 标题:Street-Level Geolocation From Natural Language Descriptions
  • 本地全文:下载
  • 作者:Nate Blaylock ; James Allen ; William de Beaumont
  • 期刊名称:Traitement Automatique des Langues
  • 印刷版ISSN:1248-9433
  • 电子版ISSN:1965-0906
  • 出版年度:2012
  • 卷号:53
  • 期号:2
  • 出版社:ATALA - Assoc Traitement Automatique Langues
  • 摘要:In this article, we describe the TEGUS system for mining geospatial path data from natural language descriptions. TEGUS uses natural language processing and geospatial databases to recover path coordinates from user descriptions of paths at street level. We also describe the PURSUIT Corpus - an annotated corpus of geospatial path descriptions in spoken natural language. PURSUIT includes the spoken path descriptions along with a synchronized GPS track of the path actually taken. Finally, we describe the performance of several variations of TEGUS (based on graph reasoning, particle filtering, and dialog) on PURSUIT.
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