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text.py
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@@ -5,8 +5,10 @@ The goal of text summarization is to condense long documents into summaries, whi
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Text summarization methods can either be used as an extractive or abstractive model. An Extractive method does what it sounds like, it concatenates different important sentences or paragraphs without understanding the meaning of those parts. Extractive summarization does not create any new word phrases. For instance, if you presented a page of text to an extractive model, it would just act as a text “highlighter”. However, Abstractive summarization generates text in a fashion that tries to guess the meaning in a summarised way of the page of text it is presented. It would put words together in a meaningful way and add the most important fact found in the text.
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<h3><center> Abstractive Model </center></h3>
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Text summarization methods can either be used as an extractive or abstractive model. An Extractive method does what it sounds like, it concatenates different important sentences or paragraphs without understanding the meaning of those parts. Extractive summarization does not create any new word phrases. For instance, if you presented a page of text to an extractive model, it would just act as a text “highlighter”. However, Abstractive summarization generates text in a fashion that tries to guess the meaning in a summarised way of the page of text it is presented. It would put words together in a meaningful way and add the most important fact found in the text.
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<figure>
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<img src="file/EX_VS_ABS.png" alt="Trulli" style="width:100%">
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<figcaption>Fig.1 - Trulli, Puglia, Italy.</figcaption>
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</figure>
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<h3><center> Abstractive Model </center></h3>
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