The document describes a system called Confomaton that aggregates social media to enhance conference experiences. Confomaton collects media items and event data from various sources, models the data semantically, and reconciles items to events in real-time. It provides a web interface and APIs to browse conferences and associated media. Future work aims to integrate more media sources, enrich event descriptions, refine reconciliation, and improve the user interface performance.

1. Aggregating Social Media for
Enhancing
Conference Experiences
Houda Khrouf , Ghislain Atemezing, Giuseppe Rizzo,
Raphaël Troncy and Thomas Steiner
Real-Time Analysis and Mining of Social Streams, 2012, Dublin, Ireland

2. What happened in ICWSM-12?
 How to get a summary?
• Spread Information
• Keyword Search
• Short life of some media
(e.g. tweets)
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3. Overview
 Create a real-time environment to browse conferences as well
as their various representative media items: images, micro-
posts, slides, videos, etc.
 Best Concept award in the "Linked Data-a-Thon" challenge of
ISWC 2011.
“Confomaton”
Semantic Web Application
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4. Confomaton architecture
Media Collector Data
(Node.js) Real-time
Reconciliation Modelling
Based on
Event Collector Tag + Named-Entity
(RSS, dumps)
Linked Data API
User Interface
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5. Media Collector
 Runs on the top of Node.js
 Collects media items and stories via search input
terms using the social media search API (Flickr,
Twitter, Slideshare, etc.)
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6. Media Collector
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7. Event Collector
 Lanyrd providing RSS feeds of about 250 conferences per month
http://lanyrd.com/conferences/
 Semantic Web Dog Food providing RDF fine-grained
descriptions of conferences:
• Sub-events (tutorials, talks, sessions, etc.)
• Papers that were presented
• People who attended and the organizations they come from.
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8. Data Modelling for Events
LODE Ontology http://linkedevents.org/ontology/
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9. Data Modelling for Media
ma:Image
http://farm7.static.flickr.com/6115% http://www.flickr.com/
2F6279003399_678b6e6e74_b.jpg people/7844118@N08
rdf:type
ma:locator
flickr: 6279009 sioc:hasCreator
lode:illustrate
sioc:Post
http://www.slideshare.net/
OlafGoerlitz/splendid- conf:iswc2011
9858478 rdf:type
lode:illustrate tweet:129568
Sioc:attachement
sioc:content
slide:627900339
sioc:hasCreator #Confomaton wins the
sioc:hasCreator rdf:type best effort at #ISWC2011
http://www.slideshare sioc:Item http://www.twitter.co
.net/OlafGoerlitz m/gatemezing
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10. Real-Time Reconciliation
Tag-based Mapping + Filtering by time
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11. Real-Time Reconciliation
If there is no tag?
 Named-Entity based Mapping
Peter Mika: RDF indexing via MapReduce,
triples are grouped into documents by
subjects #iswc2011
The paper in which the description
encapsulates these named-entities
Precision = 61%
The related event
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12. Statistics
Conferences and
Media Items
their sub-events
Semantic Web Dog Food 173 4 187
Lanyrd 1 270 572 204
And more statistics?
Conference Place Media Items
PAX East 2012 Boston 9961
SXSW Interactive 2012 Austin 9528
Hollywood spicy United States 8133
NAB Las Vegas 6831
ASTD International Conference and Exposition Denver 5962
Top-five documented conferences
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13. Technology
 RDF Storage:
 Backed up by Virtuoso (RDF triple store)
 SPARQL endpoint:
 http://eventmedia.eurecom.fr/sparql
 LDA: Linked Data API
 A set of REST methods to publish the data stored in the
RDF storage behind
 User Interface:
 HTML + CSS + Javascript
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14. Demos
http://eventmedia.eurecom.fr/confomaton
http://eventmedia.eurecom.fr/iswc2011
Conferences
Media
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15. Lessons Learned
 Easy integration of existing technologies
 Limitation of some services: e.g: max 500 requests/day
for some API
 User Interface: important BUT time consuming
 Not easy to create and manage the “all in one” interface
 How to ensure an effective navigation of a large space of
interconnected resources
 A lot of effort from Semantic Web community
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16. Future Work
 Integrate the other media services and media items
 Enrich events descriptions with further information
 Refine the reconciliation algorithm
 Improve the performance of the user interface.
 Data exploration: sentiment analysis, ranking, etc.
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17. Thank You!
http://www.slideshare.net/khrouf
E-mail: khrouf@eurecom.fr
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