1. New Approaches at Natural Language Processing Systems Zoltán ANDREJKOVICS WWW.ANDZOL.COM 2008

2. What is the basic problem of NLP?

3. モナリザ Mona Lisa With a little input

4. The system should find out more

5. There are 4 language area which are problematic

6.  Translation I love dogs. Ich liebe die Hunden.

7.  Information retrieval

8.  Understanding ≠ apple apple

9.  Searching for relations

10. How can we improve our NLP systems?

12.  Find out why people are able to do more?

13.  Current NLP systems Translation Understanding Realtion searching

15. A szakértők szerint ez a legnagyobb az eddig felfedezett kígyók között… According to these experts, it is the largest so far discovered in snakes … (hungarian news site)

16. Kikerült az App Store-ba a Ustream mobilalkalmazása … Removed from the App Store into the mobile Ustream … Ustream Viewer Added to App Store …

17.  Doesn’t understand the sentences, not searching relations  Hard to define language with rules  Google translation is stiff, language is flexible

18. A word explanation system by Viktor GYENES ≠

19. Frog? Horse, Toad, Monkey, Smile

20. Frog?

21. A word explanation system  Not broad functionality  No option to learn

22. Numenta HTM H ierarchical T emporal M emory

23. Searching pattern Searching pattern Searching pattern Searching pattern

24. Letters Words Expressions Abstract expressions

25. Letters Words Expressions Abstract expressions Aggregation

26.  Hard to fit on NLP issues  Hard to find out the aggregation algorith HTM

27.  Human knowledge and intelligence

28. What are the characteristics, that makes us a „ human ”?

29. Feelings

30. Motivation

31. Continual learning (experience)

32. When do we learn new things?

33. People want to make their world predictable

34. Situation Situation Expectation right wrong

35. If the expactation was wrong , we want to figure out another theory of the world.

36. After the review, I found some new principles

37. Knowledge depends on the person Database replaceable not replaceable Individual knowledge bases

38. Többfunkciós tudás „ analógiák” „ I bought a new tool …” „ I bought a new computer” a new machine, a new instrument, a new engine, a new camera, a new airplane etc. It means not Right understanding

39. Our knowledge fits to the problem, and not vica versa Right understanding

40. Information exchange When we eat? Sharing thoughts

41. Repeation, confirmation, exprimentation learning using knowledge learning using knowledge Continual learning

42. Motivation Unversal learning Synergy Proper motivation system Learning from any source Learning new things don’t slow the sytem

43. Next steps?

44. Finding new ways of storing data (knowledge) database, ontology, network

45. Find out how do we learn? statistical models, braing , algorithm

46. Semantic writing <item> Cat </item> <item rdf:type=&quot;animal&quot; > Cat </item>

47. System that realize what we want to do

48. Some good starts

49. FOR YOUR ATTENTION www.AndZol.com