RIA Novosti, a Russian news agency founded in 1941, developed a semantic publishing platform to generate metadata for every news item and article. This allows content to be filtered and blended for different applications and customers. The platform uses an ontology and triple store to relate entities, events, and topics across content. This enables new types of analytics and adaptive websites that personalize based on user location and interests.

1. News the New Way
Semantics in the Driver’s Seat
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

2. Philip Dudchuk
Head of Semantic Platform,
RIA Novosti
Daniel Hladky
Deputy Director, W3C Russia
Member of the Board, Ontos AG
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

3. 1941
Founded in the beginning of the WW2, RIA Novosti was
initially a news agency reporting on the situation at the
war front
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

4. First news websites looked
like simple feeds
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

5. Boom of platforms in late 2000s
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

6. Metadata rules the world of news
• News metadata gets right content to right departments of the
customer (big media)
• Metadata locates reported events (local newspapers)
• Metadata enables vertical products focused on selected areas
(banking, automotive, government)
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

7. Distinct metadata sets
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

8. 2011: Need in a common Semantic Publishing Platform
• Build and manage a common news ontology and
vocabularies for all products and news websites
• Generate metadata for every news item and every
website article
• Aggregate content and metadata for further use in end-
user applications (websites and mobile apps)
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

9. Evolution of the Publishing Cycle
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

10. The Ontology
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

11. Managing the Triple Store
Triple Store updates
• Editorial meetings
• Statistics about ‘heuristic’ entities
• Adding an entity directly from CMS
Linguistic Information in the Triple Store
• Lookups for entities
• Morphology
• Disambiguation rules & attributes
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

12. Impacts
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

13. Impact 1: Broadcasting News with Semantic Metadata
Filtering news content by triple queries at the customer’s end
(via API):
• content about any oil & gas company
• content about any employee of any public body in a
given region of Russia
• content about any event going to happen in my city
Common metadata for newswire and web content allow to
blend free and paid content into new products (news archive)
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

14. Impact 2: Adaptive Content of Websites
My ria.ru
• Locating the user and filtering the content by region
• Gathering user interests and filtering content by
entities and topics
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

15. Impact 3: Non-traditional Aggregations and Analytics
Putting together news metadata with external content
• summer forest fires
• juvenile delinquency in towns and regions
• election fraud cases
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

16. 3
21 4
10
10 2 11
3 1 12 16 3
9 1 14
11 2
1
2 12
17 1
5
Combination of crowd-sourced geo data about forest
fires and local reports by RIA Novosti
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

17. A case study: country image analysis
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

18. Country image analysis
• Searching news content related to Russia across more
than 3,000 foreign sources
• Processing search results, tagging and aggregating
content with its metadata
• Producing statistics about reaction on subjects
connected to Russia (events, people, organizations)
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

19. Negativity Index
Tymoshenko’s case in Ukraine,
threat to boycott Euro 2012
‘Pussy riots’ punks
arrested
Top sources with biggest number of negative publications on
involvement of Russian politicians and businessmen in Yulia
Tymoshenko’s case
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

20. US media on Russia’s reaction on
the events in Syria
The New York Times The Financial Times
The Washington Post
Syria’s media on the same topic
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

21. Further Challenges
• Semantic metadata for pictures and video (image
recognition)
• Processing the content from social media to create
adaptive social applications
• Adding voice recognition to semantic platform and create
new products and services incorporating video with
relevant articles and pictures
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012

22. THANK YOU!
Philip Dudchuk & Daniel Hladky
SemTechBiz, San Francisco, June 5, 2012