1. Text mining exercise
~5 m
Lars Juhl Jensen

2. the task

3. named entity recognition

4. human proteins

5. link proteins to diseases

6. what I have done

7. information retrieval

8. two diseases

9. prostate cancer

10. schizophrenia

11. two sets of documents

12. 62,755 abstracts

13. 65,588 abstracts

14. one directory with each set

15. one file with each abstract

16. dictionary

17. tab-delimited file

18. human proteins

19. 22,523 entities

20. synonyms

21. from many databases

22. orthographic variation

23. prefixes and postfixes

24. automatically generated

25. 2,726,495 names

26. tagdir program

27. flexible matching

28. upper- and lower-case

29. spaces and hyphens

30. tab-delimited output

31. what you will do

32. named entity recognition

33. find unfortunate names

34. create “black list”

35. information extraction

36. co-mentioning

37. within documents

38. link proteins to diseases

39. link between the diseases

41. a helping hand

42. “black list”

43. 100+ matches

44. 10+ matches

46. wrap up

47. prostate cancer

48. FOLH1

49. schizophrenia

50. Glutamate carboxypeptidase II

51. same protein

52. synonyms matter

53. “black list” is crucial

54. text mining is quite simple

55. diseases.jensenlab.org