Introduction to text mining

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Introduction to text mining

  1. 1. Introduction to text mining Lars Juhl Jensen >10 km
  2. 2. exponential growth
  3. 4. ~45 seconds per paper
  4. 5. text mining
  5. 6. information retrieval
  6. 7. find the relevant papers
  7. 8. user-specified query
  8. 9. “ yeast AND cell cycle”
  9. 11. entity recognition
  10. 12. identify the concepts
  11. 13. comprehensive lexicon
  12. 14. orthographic variation
  13. 15. “ black list”
  14. 16. Reflect
  15. 17. augmented browsing
  16. 18. Pafilis, O’Donoghue, Jensen et al., Nature Biotechnology , 2009
  17. 19. used by publishers
  18. 21. information extraction
  19. 22. formalize the facts
  20. 23. co-mentioning
  21. 24. NLP Natural Language Processing
  22. 25. <ul><li>Gene and protein names </li></ul><ul><li>Cue words for entity recognition </li></ul><ul><li>Verbs for relation extraction </li></ul><ul><li>[ nxexpr T he expression of [ nxgene the cytochrome genes [ nxpg CYC1 and CYC7 ]]] is controlled by [ nxpg HAP1 ] </li></ul>
  23. 26. molecular networks
  24. 28. information on side effects
  25. 29. Campillos & Kuhn et al., Science , 2008
  26. 30. Acknowledgments <ul><ul><li>Sean O’Donoghue </li></ul></ul><ul><ul><li>Sune Frankild </li></ul></ul><ul><ul><li>Heiko Horn </li></ul></ul><ul><ul><li>Evangelos Pafilis </li></ul></ul><ul><ul><li>Michael Kuhn </li></ul></ul><ul><ul><li>Reinhardt Schneider </li></ul></ul>

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