asus-aics/ntcir_13_medweb

NTCIR-13 MedWeb (Medical Natural Language Processing for Web Document) task requires to perform a multi-label classification that labels for eight diseases/symptoms must be assigned to each tweet. Given pseudo-tweets, the output are Positive:p or Negative:n labels for eight diseases/symptoms. The achievements of this task can almost be directly applied to a fundamental engine for actual applications. This task provides pseudo-Twitter messages in a cross-language and multi-label corpus, covering three languages (Japanese, English, and Chinese), and annotated with eight labels such as influenza, diarrhea/stomachache, hay fever, cough/sore throat, headache, fever, runny nose, and cold. For more information, see: http://research.nii.ac.jp/ntcir/permission/ntcir-13/perm-en-MedWeb.html As this dataset also provides a parallel corpus of pseudo-tweets for english, japanese and chinese it can also be used to train translation models between these three languages.