"Live Topic Generation from Event Streams", talk given at the Demo session of the 22nd World Wide Web Conference (WWW), Rio de Janeiro, Brazil

1. Live Topic Generation
from Event Streams
Vuk Milicic, José Luis Redondo Garcia,
Giuseppe Rizzo, Raphaël Troncy, Thomas Steiner
raphael.troncy@eurecom.fr / @rtroncy

2. Media Finder (www2013)
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3. Media Finder (zooming on media items)
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4. Media Finder (timeline view)
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5. Media Finder (timeline view)
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6. Media Server
 Composition of media item extractors (12 SNs)
 Rely on search APIs + a fix 30s timeout window to provide results
 Fallback on screen scraping when necessary (Twitter ecosystem)
 Implemented as a NodeJS server
 Serialize results in a common schema (JSON)
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Deep link
Permalink
Clean text for NLP
processing
Aggregate view of ALL
social interactions
12 Social Networks

8. Media Finder Architecture
 Media items harvesting using the Media Server
http://eventmedia.eurecom.fr/media-
server/search/{combined}/{term}
https://github.com/vuknje/media-server (@tomayac fork)
 Image near de-duplication
DCT signature on image and video frame,
Hamming distance between image pairs
 Clustering and disambiguation
Named Entity Extraction using NERD
Topic Generation using LDA
Density-based clustering using OPTICS
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9. Named Entities are Pivotal
http://nerd.eurecom.fr/
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REST API Ontology
Dashboard UI

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13. Media Finder (named entities clustering)
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14. Media Finder (zooming in a cluster)
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15. Summary
 Pick an event identified with a hashtag
 Use MediaServer to get media items
aggregated over multiple social networks
 Use NERD to get entities
aggregated over multiple extractors
 Cluster and identify meaningful topics
(aka entities)
with a meaningful label
often disambiguated with a DBpedia URI giving access
to more encyclopedic knowledge
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16. Live Topic Generation from Event Streams
 Meet us at WWW 2013 Demo Session, Booth 14
http://www.youtube.com/watch?v=8iRiwz7cDYY
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17. http://www.slideshare.net/troncy
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