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Spatial characteristics of a large web n-gram corpus


Sautier, Jerome; Derungs, Curdin (2015). Spatial characteristics of a large web n-gram corpus. In: GIR '15 9th Workshop on Geographic Information Retrieval, Paris, 26 November 2015 - 27 November 2015, online.

Abstract

N-gram corpora, though prominently used to structure and index large natural language corpora, are rarely in the focus of GIR. In this study we describe a step in this direction by characterizing spatial information in a large Web n-gram corpus provided by Microsoft. We explore how continent and country toponyms are represented in this corpus and if basic topological relations can be correctly retrieved. Results suggest that toponym ambiguity has major impact and that although retrieved topological relations are often correct, recall is considerably low. We conclude that further research is required if more fine grained spatial information is to be retrieved from n-grams.

Abstract

N-gram corpora, though prominently used to structure and index large natural language corpora, are rarely in the focus of GIR. In this study we describe a step in this direction by characterizing spatial information in a large Web n-gram corpus provided by Microsoft. We explore how continent and country toponyms are represented in this corpus and if basic topological relations can be correctly retrieved. Results suggest that toponym ambiguity has major impact and that although retrieved topological relations are often correct, recall is considerably low. We conclude that further research is required if more fine grained spatial information is to be retrieved from n-grams.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), not refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
08 University Research Priority Programs > Language and Space
Dewey Decimal Classification:910 Geography & travel
Language:English
Event End Date:27 November 2015
Deposited On:20 Jan 2016 13:55
Last Modified:17 Aug 2017 16:28
Publisher:ACM Digital Library
Publisher DOI:https://doi.org/10.1145/2837689.2837691

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