Automatic summarization extraction

Main Information
This field is optional but you should use it to get better results

  • TF: Term Frequency
  • ISF: Inverse Sentence Frequency, rewards the low frequency of words inside a document's sentences.
  • IDF: Inverse Document Frequency, rewards the low frequency of words inside a documents library.
  • RIDF: Residual IDF, rewards the low appearance probability of words inside our text.
TF-ISF is a lightweigh solution, TF-IDF & TF-RIDF use the internal documents and terms libraries to calculate the scores. TF-RIDF uses the Poison model to calculate the probabilities of the terms.
The sentences that exceed the words limits will be ingored. The 0 disables the limit.
Advance Options
  • The Article method ranks higher top paragraphs/sentence.
  • The Baxendale's method ranks higher the first and last sentences in a paragraph.
  • Sentence(i) Score = TW * T(i) + PW * P(i) + KW * K(i).
  • The T, P, K are each sentence's terms score, position score and keywords score.
  • The TW, PW, KW are the weights for linear combination of the three scores.
  • The weights are unsigned float values, set a weight to 0 to disable.
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