Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Modelling vague places with knowledge from the Web

Jones, Christopher Bernard, Purves, R. S., Clough, P. D. and Joho, H. 2008. Modelling vague places with knowledge from the Web. International Journal of Geographical Information Science 22 (10) , pp. 1045-1065. 10.1080/13658810701850547

Full text not available from this repository.

Abstract

Place names are often used to describe and to enquire about geographical information. It is common for users to employ vernacular names that have vague spatial extent and which do not correspond to the official and administrative place name terminology recorded within typical gazetteers. There is a need therefore to enrich gazetteers with knowledge of such vague places and hence improve the quality of place name‐based information retrieval. Here we describe a method for modelling vague places using knowledge harvested from Web pages. It is found that vague place names are frequently accompanied in text by the names of more precise co‐located places that lie within the extent of the target vague place. Density surface modelling of the frequency of co‐occurrence of such names provides an effective method of representing the inherent uncertainty of the extent of the vague place while also enabling approximate crisp boundaries to be derived from contours if required. The method is evaluated using both precise and vague places. The use of the resulting approximate boundaries is demonstrated using an experimental geographical search engine.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords: Gazetteers, Geographical information retrieval, Geo‐parsing, Surface modelling, Vagueness
Publisher: Taylor & Francis
ISSN: 1365-8816
Last Modified: 04 Jun 2017 02:56
URI: http://orca-mwe.cf.ac.uk/id/eprint/14140

Citation Data

Cited 135 times in Google Scholar. View in Google Scholar

Cited 130 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item