The CHEMDNER corpus of chemicals and drugs and its annotation principles.
Martin KrallingerObdulia RabalFlorian LeitnerMiguel VazquezDavid SalgadoZhiyong LuRobert LeamanYanan LuDonghong JiDaniel M. LoweRoger A. SayleRiza Theresa Batista-NavarroRafal RakTorsten HuberTim RocktäschelSérgio MatosDavid CamposBuzhou TangHua XuTsendsuren MunkhdalaiKeun Ho RyuS. V. RamananP. Senthil NathanSlavko ZitnikMarko BajecLutz WeberMatthias IrmerSaber A. AkhondiJan A. KorsShuo XuXin AnUtpal Kumar SikdarAsif EkbalMasaharu YoshiokaThaer M. DiebMiji ChoiKarin VerspoorMadian KhabsaC. Lee GilesHongfang LiuRavikumar Komandur ElayavilliAndre LamuriasFrancisco M. CoutoHong-Jie DaiRichard Tzong-Han TsaiCaglar AtaTolga CanAnabel UsieRui AlvesIsabel Segura-BedmarPaloma MartínezJulen OyarzabalAlfonso ValenciaPublished in: J. Cheminformatics (2015)
Keyphrases
- annotated corpus
- automatic annotation
- hand crafted
- semantic annotation
- manually annotated
- image annotation
- open domain
- named entities
- metadata
- design principles
- inter annotator agreement
- drug discovery
- knowledge base
- data sets
- automatic image annotation
- high throughput
- theoretical framework
- test set
- video annotation
- linguistic features
- active learning
- machine learning
- spanish language
- neural network