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Named entity recognition (NER) is highly sensitive to sentential syntactic and semantic properties where entities may be extracted according to how they are used and placed in the running text. To model such properties, one could rely on existing res
Externí odkaz:
http://arxiv.org/abs/2010.15466
Existing approaches for named entity recognition suffer from data sparsity problems when conducted on short and informal texts, especially user-generated social media content. Semantic augmentation is a potential way to alleviate this problem. Given
Externí odkaz:
http://arxiv.org/abs/2010.15458
Akademický článek
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Akademický článek
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Autor:
Chen, Yanquan, Nie, Yuyang
A human individual's interaction time with multimedia mediums has reach its history peak and is still increasing. The demand for more personalized, automated, and energy efficient multimedia technologies becomes one of the top researched areas in com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______166::6e8f43619711ffcca2a0b5415985c284
https://hal.archives-ouvertes.fr/hal-03606641
https://hal.archives-ouvertes.fr/hal-03606641
Publikováno v:
Health & Medicine Week; 2/16/2024, p10065-10065, 1p
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