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@@ -28,7 +28,7 @@ The dataset is composed of 400 abstracts of scientific papers in French collecte
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  Keyphrases were annotated by professional indexers in an uncontrolled setting (that is, not limited to thesaurus entries).
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  Details about the dataset can be found in the original paper [(Bougouin et al., 2016)][bougouin-2016].
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- Reference (indexer-assigned) keyphrases are also categorized under the PRMU (<u>P</u>resent-<u>R</u>eordered-<u>M</u>ixed-<u>U</u>nseen) scheme as proposed in [(Boudin and Gallina, 2021)][boudin-2021].
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  Text pre-processing (tokenization) is carried out using `spacy` (`fr_core_news_sm` model) with a special rule to avoid splitting words with hyphens (e.g. graph-based is kept as one token).
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  Stemming (Snowball stemmer implementation for french provided in `nltk`) is applied before reference keyphrases are matched against the source text.
 
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  Keyphrases were annotated by professional indexers in an uncontrolled setting (that is, not limited to thesaurus entries).
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  Details about the dataset can be found in the original paper [(Bougouin et al., 2016)][bougouin-2016].
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+ Reference (indexer-assigned) keyphrases are also categorized under the PRMU (<u>P</u>resent-<u>R</u>eordered-<u>M</u>ixed-<u>U</u>nseen) scheme as proposed in [(Boudin and Gallina, 2021)][boudin-2021]. Present reference keyphrases are also ordered by their order of apparition in the concatenation of title and abstract.
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  Text pre-processing (tokenization) is carried out using `spacy` (`fr_core_news_sm` model) with a special rule to avoid splitting words with hyphens (e.g. graph-based is kept as one token).
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  Stemming (Snowball stemmer implementation for french provided in `nltk`) is applied before reference keyphrases are matched against the source text.