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README.md
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## According to the abstract of the literature review,
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We provide a literature review about Automatic Text Summarization systems. We consider a citation-based approach. We start with some popular and well-known
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papers that we have in hand about each topic we want to cover and we have tracked the "backward citations" (papers that are cited by the set of papers we
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knew beforehand) and the "forward citations" (newer papers that cite the set of papers we knew beforehand). In order to organize the different methods, we
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present the diverse approaches to ATS guided by the mechanisms they use to generate a summary. Besides presenting the methods, we also present an extensive
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review of the datasets available for summarization tasks and the methods used to evaluate the quality of the summaries. Finally, we present an empirical
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exploration of these methods using the CNN Corpus dataset that provides golden summaries for extractive and abstractive methods.
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This model was an end-result of the above mentioned literature review paper, from which the best solution was drawn to be applied to the problem of
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summarizing texts extracted from the Research Financing Products Portfolio (FPP) of the Brazilian Ministry of Science, Technology, and Innovation (MCTI).
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## According to the abstract of the literature review,
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24 |
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25 |
+
- We provide a literature review about Automatic Text Summarization systems. We consider a citation-based approach. We start with some popular and well-known
|
26 |
+
papers that we have in hand about each topic we want to cover and we have tracked the "backward citations" (papers that are cited by the set of papers we
|
27 |
+
knew beforehand) and the "forward citations" (newer papers that cite the set of papers we knew beforehand). In order to organize the different methods, we
|
28 |
+
present the diverse approaches to ATS guided by the mechanisms they use to generate a summary. Besides presenting the methods, we also present an extensive
|
29 |
+
review of the datasets available for summarization tasks and the methods used to evaluate the quality of the summaries. Finally, we present an empirical
|
30 |
+
exploration of these methods using the CNN Corpus dataset that provides golden summaries for extractive and abstractive methods.
|
31 |
|
32 |
This model was an end-result of the above mentioned literature review paper, from which the best solution was drawn to be applied to the problem of
|
33 |
summarizing texts extracted from the Research Financing Products Portfolio (FPP) of the Brazilian Ministry of Science, Technology, and Innovation (MCTI).
|