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A corpus for mining drug-related knowledge from Twitter chatter: Language models and their utilities
In this data article, we present to the data science, natural language processing and public heath communities an unlabeled corpus and a set of language models. We collected the data from Twitter using drug names as keywords, including their common misspelled forms. Using this data, which is rich in...
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| Wydane w: | Data Brief |
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| Główni autorzy: | , |
| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
Elsevier
2016
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| Hasła przedmiotowe: | |
| Dostęp online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5144647/ https://ncbi.nlm.nih.gov/pubmed/27981203 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.dib.2016.11.056 |
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