Semantic Similarities between Locations based on Ontology
| Authors | |
|---|---|
| Year of publication | 2017 |
| Type | Article in Proceedings |
| Conference | Proceedings of the Eleventh Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2017 |
| MU Faculty or unit | |
| Citation | SHERWANI, Moiz Khan; Petr SOJKA and Francesco CALIMERI. Semantic Similarities between Locations based on Ontology. In Aleš Horák, Pavel Rychlý, Adam Rambousek. Proceedings of the Eleventh Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2017. Brno: Tribun EU, 2017, p. 85-94. ISBN 978-80-263-1340-3. |
| web | |
| Field | Informatics |
| Keywords | toponym disambiguation; geonames; geographic text retrieval; ontology based geoname relations; toponym similarity |
| Description | Toponym disambiguation or location names resolution is a critical task in unstructured text, articles or documents. Our research explores how to link ambiguous locations mentioned in documents, news and articles with latitude/longitude coordinates. We designed an evaluation system for toponym disambiguation based on annotated GEOCLEF data. We implemented a node-based approach taking population into account and a geographic distance-based approach. We have proposed new approach based on edges between the pairs of toponyms in ontology, taking also population attribute into account. Our edge-based approach gave better results than population and distance-based only approaches. The results could be used in any information system dealing with texts containing geographic locations, such as news texts. |
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