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Location approximation for local search services using natural language hints

Schockaert, Steven, De Cock, M. and Kerre, E. E. 2008. Location approximation for local search services using natural language hints. International Journal of Geographical Information Science 22 (3) , pp. 315-336.

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Abstract

Local search services allow a user to search for businesses that satisfy a given geographical constraint. In contrast to traditional web search engines, current local search services rely heavily on static, structured data. Although this yields very accurate systems, it also implies a limited coverage, and limited support for using landmarks and neighborhood names in queries. To overcome these limitations, we propose to augment the structured information available to a local search service, based on the vast amount of unstructured and semi-structured data available on the web. This requires a computational framework to represent vague natural language information about the nearness of places, as well as the spatial extent of vague neighborhoods. In this paper, we propose such a framework based on fuzzy set theory, and show how natural language information can be translated into this framework. We provide experimental results that show the effectiveness of the proposed techniques, and demonstrate that local search based on natural language hints about the location of places with an unknown address, is feasible.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Publisher: Taylor & Francis
ISSN: 1365-8816
Last Modified: 04 Jun 2017 04:03
URI: http://orca.cf.ac.uk/id/eprint/31819

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