Authors:
Andrei Tabarcea
1
;
Ville Hautamäki
2
and
Pasi Fränti
3
Affiliations:
1
Technical University of Iaşi, Romania
;
2
Institute for Infocomm Research, A*STAR, Singapore
;
3
Speech and Image Processing Unit, University of Eastern Finland, Finland
Keyword(s):
Search engine, LBS, Database, Prefix tree, Georeferencing, Mobile device, Location information, Personal navigation, WWW.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Searching and Browsing
;
Soft Computing
;
Symbolic Systems
;
Web Geographical Information Systems
;
Web Information Systems and Technologies
;
Web Interfaces and Applications
;
Web Mining
Abstract:
A bottleneck of constructing location-based web searches is that most web-pages do not contain any explicit geocoding such as geotags. Alternative solution can be based on ad-hoc georeferencing which relies on street addresses, but the problem is how to extract and validate the address strings from free-form text. We propose a rule-based solution that detects address-based locations using a gazetteer and street-name prefix trees created from the gazetteer. We compare this approach against a method that doesn’t require a gazetteer (a heuristic method that assumes that street-name has a certain structure) and a method that also uses data structures created from the gazetteer in the form of street-name arrays. Experiments using our location based search engine prototype (MOPSI) for Finland and Singapore, show that the proposed prefix-tree solution is twice as fast and 10% more accurate than its rule-based alternative and 10 times faster if an array structure is used when accessing the g
azetteer.
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