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Financial News Term Extraction Techniques

Explore term extraction from financial news, analyzing metrics like Frequency, Conditional Probability, and Mutual Information. Identify uni-grams, bi-grams, tri-grams based on frequency and MI values. Learn about Extreme Status indicators and potential further work like PAT-Tree and Pattern Filter.

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Financial News Term Extraction Techniques

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  1. Term Extraction from Financial News Jian-Shiun 2008/10/31

  2. Financial News－鉅亨網

  3. Data Collection • Period：2008/10/10 ~ 2008/10/30 • Number of news：1,987

  4. Accumulated Grams

  5. grams docs

  6. Metrics • Frequency • Conditional Probability • Mutual Information

  7. Mutual Information • If f(w) ≥ f(c1) f(c2)… f(cn), then Mi(w) ≥ 0

  8. uni-gram (first 60 by freq)

  9. bi-gram (first 30 by freq, MI>0)

  10. bi-gram (first 30 by freq, MI<0)

  11. tri-gram (first 30 by freq , MI>0)

  12. tri-gram (first 30 by freq , MI<0)

  13. 4-gram (first 30 by freq , MI>0)

  14. 5-gram (first 30 by freq , MI>0)

  15. Extreme Status Using MI • f(w) is very low, and MI is very high＊ • f(w) is very low, and MI is very low • f(w) is very high, and MI is very high＊ • f(w) is very high, and MI is very low

  16. 1. f(w) is very low, and MI is very high＊

  17. 2. f(w) is very low, and MI is very low

  18. 3. f(w) is very high, and MI is very high＊

  19. 4. f(w) is very high, and MI is very low

  20. Further Work • PAT-Tree • Pattern Filter • Cross Validate with CKIP

  21. Reference • 劉開瑛(2000)，中文文本自動分詞和標註，北京：商務印書館。

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