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As you know extractive text summarization is a binary classification problem!(a sentence should be included in summary or not). we have developed our text summarization system with three different algorithms and evaluated them with ROUGE. here is our result

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My question is which parametes is more important in text summarization systems. As you can see model 1 has higher recall but lower precision and model 2 has lower recall but higher precision so which one should be selected as the best model?

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as you know text summarization is a binary classification problem!(a sentence should be included in summary or not).

This is extractive text summarization.

model 2 has lower recall but higher precision

I assume you meant model 3

which one should be selected as best model?

That depends on the user needs: sometimes it is preferable to have a bit too many sentences that somehow overlap, sometimes it is preferable to have a short summary potentially skipping important sentences.

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