Here are the slides from the Agora presentation at Museums and the Web 2011. Johan Oomen and Marieke van Erp presented this first version of the Agora event extraction system to enrich museum collection with during the Linked Data Session on Thursday 7 April 2011. For more information see http://agora.cs.vu.nl

1. Automatic Heritage Metadata
Enrichment with Historic Events
Marieke van Erp, Johan Oomen, Roxane Segers, Chiel van den
Akker, Lora Aroyo, Geertje Jacobs, Susan Legêne, Lourens van
der Meij, Jacco van Ossenbruggen and Guus Schreiber
http://agora.cs.vu.nl
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2. The Agora Project
• 2009-2013
• VU Amsterdam (CS + History Departments),
Netherlands Institute for Sound and Vision, Rijksmuseum
Amsterdam
• Funded by the Netherlands Organisation for Scientific
Research (NWO) within the CATCH research
programme
MW2011
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3. “Enabling anything like seamless access to the cultural record
will require developing tools to navigate among vast catalogs of
born-digital and digitized materials, […]
The return on this investment will be a humanities and social
science cyberinfrastructure that will allow new questions to be
asked, new patterns and relations to be discerned, and deep
structures in language, society, and culture to be exposed and
explored.”
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http://www.acls.org/programs/Default.aspx?id=644

4. Gabriel Metsu
(17th century Dutch painer)
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5. 7/4/11 Venue

6. Networked heritage
?
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7. Europeana ~15,578,850
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8. Europeana Thoughtlab
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9. Europeana Thoughtlab
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10. Baseline: matching
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11. Baseline: matching
Metadata for the
object
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12. Baseline: matching
Metadata for the
object
Controlled place name
from a vocabulary at the
Rijskmuseum
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13. A "more specific Egypt"?
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14. 7/4/11 Venue

15. date Venue

16. were present at…
date Venue

17. date Venue

18. Location is...
date Venue

19. date Venue

20. role is…
date Venue

21. date Venue

22. is part of…
date Venue

23. why enrichment?
• Historical context is missing
• What happened before/after
• ‘Grand narratives’
• Based on keyword search
• Exact matches
• ...and manual annotation is costly
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24. http://www.bl.uk/learning/timeline/
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25. Simple Event Model
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26. The Pipeline
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27. The Pipeline
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28. Recognising Events
• Pattern-based approach to find Event
names
• “during the” <NP>
• “after the” <NP>
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29. Recognising Events
• Machine learning based approach to
recognise persons and locations
• Retrained Stanford NER system for
Dutch
• Regular expressions to recognise temporal
expressions
• [0-9]{1,2}/[0-9]{1,2}/[0-9]{4}
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30. The Pipeline
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31. Linking Event Elements
• Check which pairs of event names and
persons, locations or times co-occur most
within a Wikipedia paragraph
• Rank by most frequent
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32. The Pipeline
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33. Event Instances
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34. Thesaurus 1 Thesaurus 2 Direct Links Links Via
Events
Rijksmuseum Sound and
- 20
events Vision locations
Rijksmuseum Sound and
- 15
events Vision people
Rijksmuseum Sound and
- 300
people Vision locations
Rijksmuseum Sound and
7 297
locations Vision people
Rijksmuseum Rijksmuseum
488
events locations
Rijksmuseum Rijksmuseum
395
events people
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35. New Links
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36. Event-driven Browsing
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37. Conclusions
• Events provide a framework for collection
data enrichment
• Language technology can be used to
identify events
• Events provide meaningful links between
different collections
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38. Future Work
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39. Future Work
• Fine-tuning event extraction approach
• English version of the system
• User involvement to improve event
relations
• User-generated narratives
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40. ? ?
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?
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41. credits
• publications etc. http://agora.cs.vu.nl
• Merci Web & Media Group at VU University
for inspiration & images
• Follow us on Twitter
• @agoraproject
• @johanoomen
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