GIR'16 Workshop Semantic; Folksonomy; Geographic Information; Coverage; VGI

1. Centre Universitaire d’Informatique
Institute of Information Service Science
Seman&c enrichment of places
with VGI sources: a knowledge
based approach
Tardy, C., Falquet, G., Moccozet, M.
Workshop GIR’16 – SIG Spa2al 2016
November 2016 - San Francisco, California, USA

2. Problem Statement
How to use social media tags to iden2fy places and their
characteris2cs?
• Using picture tags
• Categoriza?on algorithm
• based on geographic and terminological knowledge
resources
• not a sta?s?cal approach
• For places with small number of data
Tardy et al., University of Geneva 2

3. Example
Characteris&cs
• Music / Musique
• Concert / Gigs
• Shows
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hJps://flic.kr/p/m9ZBPB
Places
• Geneva/Genève
• Switzerland
• Plainpalais
• Carouge
• Alpes/Alps
• Chat Noir
• Théatre Pitoëff
• Canada

4. Method
Tag ti
Geo weight
gw(ti)
Sense & Category
{ti, sensei, cati}
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geo
process
word sense
process
Disambigua?on
1. Find ngw(ti)
2. Compare weights
Dispatch tag
Geo OR non Geo
Geo coverage
Characteris?cs
Discard

5. Geo Process
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6. Localisa?on Example
Flickr photo loca?on info :
<loca&on la&tude="46.193959" longitude="6.143385” accuracy="16"
context="0" place_id="EDcBbVFWWrj07WE” woeid="782861”>
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7. Word Sense Process
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8. Disambigua?on
Tardy et al., University of Geneva 8

9. Tags Extrac?on
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10. Example
Actor
Event Temporal
Color Uniden&fied
“Seman&c Enhancement of
Places” (SEP) tags :
• Ambiance
• Nightlife
• Music / Musique
• Concert / Gigs
• Shows
• Fes?val
• ASMV
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In geo coverage :
à Théâtre Pitoëff
Geographic feature /
Geographic feature class
hJps://flic.kr/p/m9ZBPB

11. Tes?ng
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hJps://flic.kr/p/qnvRLa

12. Results
• 142 photos
• 3 validators
• 2 data sets in Geneva area, Switzerland
• Mul?-label precision-recall :
o precision = 72.5%;
o recall = 66.7%;
o F-measure = 0.695
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13. Conclusion
• A technique that combines geographical knowledge and the
extrac?on of text seman?cs
• Evalua?ons show that the technique is effec?ve
– Can be used to enhance spa?al descrip?ons in geo-services (Citygml,
OpenStreetMap)
– Works on geographic zones with low density of resources
Future explora?ons
• Use it as a pre-treatment to sta?s?cal approach
• Refine the analysis for photos describing mul?ple geo features
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