TF-IDF: Difference between revisions

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| new || 1/7 || Log(2/1) = 0.3 || 0.04
| new || 1/7 || Log(2/1) = 0.3 || 0.04
|-
|-
| car || 3/7 || Log(2/1) = 0.3 || '''0.13'''
| '''car''' || 3/7 || Log(2/1) = 0.3 || '''0.13'''
|-
|-
| used || 1/7 || Log(2/1) = 0.3 || 0.04
| used || 1/7 || Log(2/1) = 0.3 || 0.04
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| a || 2/8 || Log(2/2) = 0 || 0
| a || 2/8 || Log(2/2) = 0 || 0
|-
|-
| friend || 2/8 || Log(2/1) = 0.3 || 0.08
| '''friend''' || 2/8 || Log(2/1) = 0.3 || '''0.08'''
|-
|-
| in || 1/8 || Log(2/1) = 0.3 || 0.04
| in || 1/8 || Log(2/1) = 0.3 || 0.04

Revision as of 08:29, 28 December 2019

Term Frequency - Inverse Document Frequency

TF Score

TF = 단어의 출현 수 / 총 단어의 개수
  • a new car, used car, car review
    • TF Score를 통해 car가 중요한 단어라는 것을 확인하였음
단어 TF Score
a 1/7
new 1/7
car 3/7
used 1/7
review 1/7
  • a friend in need is a friend indeed
    • TF Score를 측정했는데 Friend와 a가 동일한 중요도로 산출됨
    • 이런 경우를 보완하기 위해 IDF 사용
단어 TF Score
a 2/8
friend 2/8
in 1/8
need 1/8
is 1/8
indeed 1/8

IDF

IDF = Log (이 단어가 사용된 문장의 수 / 총 문장의 수+1)
  • TF에 IDF를 적용하면, a/the/in/is 와 같은 의미 없는 불용어를 희석시킬 수 있다.
단어 TF Score IDF Score TF * IDF
a 1/7 Log(2/2) = 0 0
new 1/7 Log(2/1) = 0.3 0.04
car 3/7 Log(2/1) = 0.3 0.13
used 1/7 Log(2/1) = 0.3 0.04
review 1/7 Log(2/1) = 0.3 0.04
a 2/8 Log(2/2) = 0 0
friend 2/8 Log(2/1) = 0.3 0.08
in 1/8 Log(2/1) = 0.3 0.04
need 1/8 Log(2/1) = 0.3 0.04
is 1/8 Log(2/1) = 0.3 0.04
indeed 1/8 Log(2/1) = 0.3 0.04