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TALP-UPC at MediaEval 2014 Placing Task: Combining geographical knowledge bases and language models for large-scale textual georeferencing

Author
Ferres, D.; Rodriguez, H.
Type of activity
Presentation of work at congresses
Name of edition
MediaEval 2014 - Multimedia Benchmark Workshop
Date of publication
2014
Presentation's date
2014-10
Book of congress proceedings
Working Notes Proceedings of the MediaEval 2014 Workshop
First page
1
Last page
2
Publisher
CEUR-WS.org
Project funding
Adquisición de escenarios de conocimiento a través de la lectura de textos: inferencia de relaciones entre eventos (SKATeR)
Repository
http://hdl.handle.net/2117/25611 Open in new window
URL
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_77.pdf Open in new window
Abstract
This paper describes our Georeferencing approaches, experiments, and results at the MediaEval 2014 Placing Task evaluation. The task consists of predicting the most probable geographical coordinates of Flickr images and videos using its visual, audio and metadata associated features. Our approaches used only Flickr users textual metadata annotations and tagsets. We used four approaches for this task: 1) an approach based on Geographical Knowledge Bases (GeoKB), 2) the Hiemstra Language Model (HL...
Citation
Ferrés, D.; Rodríguez, H. TALP-UPC at MediaEval 2014 Placing Task: Combining geographical knowledge bases and language models for large-scale textual georeferencing. A: Multimedia Benchmark Workshop. "Working Notes Proceedings of the MediaEval 2014 Workshop". Barcelona: CEUR-WS.org, 2014, p. 1-2.
Keywords
Associated feature, Geographical coordinates, Knowledge basis, Language model, Margin of error, Research center, Research groups, Textual metadata
Group of research
GPLN - Natural Language Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
TALP - Centre for Language and Speech Technologies and Applications

Participants

Attachments