Predicting P & R
by
Term Variability &
Word Sense Ambiguity


 Farzaneh Sarafraz

5 March 2010
What do the following things
    have in common?
EARRING STEMS
ARMY ENCAMPMENTS
STAFF
POSITION
BLOG
ARTICLE
TRADING STATION
Post
Polysemy – Word Sense Ambiguity




                        A
Term Variability


                   A
                   B
                   C
Term Variability Measure


                # different words
    V [class ]=
                # all mentions




       AAB...
Word Entropy


                       #  word ,class            #  word , class
H [ word ]=− ∑                       ...
Class Entropy
                           # word , class
  H [class ]= ∑ H [word ].
             word ∈class   # * , cla...
Guess

          Lexical Variability
                                R
        AABBBBCCAAAAAAC


 Class Characterisability...
Precision vs. Class Confusion
      100


              Protein Catabolism
       90

      Phosphorylation

       80


 ...
Recall vs. Lexical Variability
      120




      100           Phosphorylation




                                     ...
Results For Other Teams




                                 Average precision vs. class
Average recall vs. variability   ...
Ideas, please?
Information Extraction


  K J G T C S H U A G Y X W.
Information Extraction


  K J G T C S H U A G Y X W.
Information Extraction


  K J G T C S H U A G Y X W.
Information Extraction


  K J G T C S H U A G Y X W.
Ambiguity
Ambiguity
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Ambiguity

  1. 1. Predicting P & R by Term Variability & Word Sense Ambiguity Farzaneh Sarafraz 5 March 2010
  2. 2. What do the following things have in common?
  3. 3. EARRING STEMS
  4. 4. ARMY ENCAMPMENTS
  5. 5. STAFF POSITION
  6. 6. BLOG ARTICLE
  7. 7. TRADING STATION
  8. 8. Post
  9. 9. Polysemy – Word Sense Ambiguity A
  10. 10. Term Variability A B C
  11. 11. Term Variability Measure # different words V [class ]= # all mentions AABBBBCCAACAAAAAAAAAC
  12. 12. Word Entropy #  word ,class  #  word , class H [ word ]=− ∑  . log 2   allclasses #  word ,* #  word ,*  A
  13. 13. Class Entropy # word , class H [class ]= ∑ H [word ]. word ∈class # * , class Class [Un]-characterisability / Confusion # word , *−class # word , class C [class]= ∑  .  word ∈ class # word , * # * , class
  14. 14. Guess Lexical Variability R AABBBBCCAAAAAAC Class Characterisability A P B
  15. 15. Precision vs. Class Confusion 100 Protein Catabolism 90 Phosphorylation 80 70 Regulation Gene Expression 60 Binding Positive Regulation 50 Localization Negative Regulation 40 30 Transcription 20 10 0 0 0.05 0.1 0.15 0.2 0.25 0.3 Correlation = -0.72
  16. 16. Recall vs. Lexical Variability 120 100 Phosphorylation Protein Catabolism 80 Gene Expression Localization Transcription 60 40 Binding Negative Regulation 20 Positive Regulation Regulation 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 Correlation = -0.68
  17. 17. Results For Other Teams Average precision vs. class Average recall vs. variability confusion Correlation = -0.82 Correlation = 0.03
  18. 18. Ideas, please?
  19. 19. Information Extraction K J G T C S H U A G Y X W.
  20. 20. Information Extraction K J G T C S H U A G Y X W.
  21. 21. Information Extraction K J G T C S H U A G Y X W.
  22. 22. Information Extraction K J G T C S H U A G Y X W.

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