Tech talk about Zemanta's st

1. Audible Tech Talk
23. April 2012
Andraz Tori
andraz@zemanta.com
@andraz

2. Today's plan
• Short story of Zemanta
• The Zemanta technology

3. Where am I right now?

4. Wonders of modern
communication

5. Ljubljana

6. Strip mine
• A system for Slovenian National television in 2006
• Closed captioning → web page for each episode of
each show
• Natural Langauge Processing, Information
Retrieval...

7. Start-up? Why not?
v

8. Tour de Slovénie

9. Sales

11. Seedcamp
• First European program inspired by YC (2007)
• London based
• 3 months, 50.000 EUR / 10%

13. Roller coaster
12. August Deadline
20. August Shortlist
23. August Phone interview
24. August Results
3. September London week start
7. September London week end
16. September ==> London

14. 3 months in London

17. Back to Ljubljana

18. Back to Ljubljana

20. And then ...
• Figuring out US is our target market
• Figuring out where in US to be and who to have here
• Partnerships
• And naturally the business model

21. Technology

22. What do we do?
• Zemanta – Personal Writing Assistant
- on your current platform
• While bloggers write we suggest:
- images
- related articles
- in-text links
- tags

26. Some stats
• 80k bloggers monthly
• 1.3 million posts enhanced in 2011

27. How does it work
• Natural Language Processing
• Big database of “meanings” (entities, concepts, topics)
• Word Sense Disambiguation
• Linking out to Wikipedia, Freebase, …
• Categorization, Named Entity Recognition
• Information Retrieval
• Solr based, using features from NLP
• With some twists

28. Indexed content
Content
suggestions
Plain text Semantic
(article) Analysis
search
Background
knowledge

29. “Text Understanding”
- Input is meaningful chunk of text (not a keyword or a
phrase)
- Input is (semi) English language
- Has to work across all domains in the open world
- music, celebrities, finance, entertainment, politics,
gardening, parenting, …

30. Indexed content
Content
suggestions
Plain text Semantic
(article) Analysis
search
Background
knowledge

31. Background knowledge
- Data from Wikipedia, MusicBrainz, Freebase… and the
world wild web
- Includes linguistical and semantical properties and
unstructured data
- Present in two forms:
- in “original” custom built triple store on top of MySQL
(150 GB)
- processed into 7 GB optimized “memory mapped
dump”

32. Analysis pipeline
Known phrases
Named Entity
extraction
Extraction
(aho-corasick)
Triple store
Surface form features evaluation
Statistical comparison to
background knowledge
Semantic coherence
and hand-tuned
heuristics
etc.
Disambiguated entities

33. Indexed content
Content
suggestions
Plain text Semantic
(article) Analysis
search
Background
knowledge

34. Connecting content
• Indexing blogosphere and mediasphere
• Solr based index
• Twist: complicated queries – 50 terms
• Filtering out spam is “fun”
• Probably best “related content” in terms of accuracy
• Coming soon: social signal

35. But why just for bloggers?
Let's open up the API!

36. Some API users

37. Back to reality.

38. Age of “smart”

39. Blog me up, Scotty!
23. April 2012

40. Some takeaways
• Accelerators are good
• World is getting flatter
But it will never be flat
• Start monetizing soon – to learn, not to earn
• Be where your market is
• Many markets left to innovate in

41. Thank you!