Handwritten Text Recognition for manuscripts and early printed texts
SemTech09 European Day: presentation by NoTube
1.
2. FP7 Integrated Project
• Networks and ontologies for the transformation and
unification of broadcasting and the Internet
• Research
• Broadcast & Telecommunication
• Industry
• Dissemination & Training
3. getting personal with your TV
• Semantic technology to realize new level of
service for context-dependent and personalized
selection of TV content
• Community to bring content consumption from a
single-user activity to a community-based
experience
• Distributed personalization in distributed,
interactive and multi-device environment
4. who will benefit
• viewers: gain control over TV-entertainment;
classical mass-media broadcasting changes by
users‘ Social Web engagement
• providers: information integration in a TV-
Internet environment for personalized content
delivery
• advertisers: a contextualized and personalized
TV-based narrowcasting
5. demonstrators
• Personalized semantic
news
• Personalized TV guide
with adaptive
advertising
• Internet TV in the
Social Web
9. Internet TV in Social Web
Friends following this event
Friends following this event
Billy
That was
never a
corner..
Friends following this event
Friends following this event
10. Internet TV in Social Web
Friends following this event
Tom
Billy
That was
never a
corner..
Full screen
Friends following this event
Friends following this event
11. Bean counter & Recommender
• Bean Counter
– Attention data
aggregation
– Interest profile
generation
– Accessible via APIs
• Recommender
– Accessible via APIs
– Visualisation as EPG
13. Web-service-based metadata
exchange components
• vocabulary alignment, semantic annotation
– ClioPatria, http://e-culture.multimedian.nl/software/ClioPatria.shtml
– NoTube vocabularies (few examples):
– VU event ontology, BBC event ontology
– OntoMedia Core, FOAF, Web ofTtrust
– wsml.rdf wsmo-lite.rdf wsmo.rdf
– IMDB, Music ontology, Programs ontology
– dbpedia, WordNet
– W3C time ontology
14. distributed personalization
• context-aware user modelling
– on different terminals
– recommendations of TV content
– personalized ads
• personalized presentation
– switching between devices
– multimedia content
– user profiles
15.
16. personalization focus
• Collection of attention data
• Derive interests from attention data
• Surface programs of interest in the ‘long tail’
• Cross-domain recommendations
• Multi-person recommending
• Granular control for users
17.
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20.
21. Acknowledgements
• Chris van Aart • Lyndon Nixon
• Dan Brickley • Davide Palmisano
• Stefan Dietze • Yves Raimond
• Eylem Kehribar • Guus Schreiber
• HyoMin Kim • Ronald Siebes
• Libby Miller • Jan Wielemaker
• Michele Minno • … other NoTube partners
