An attention-based BiLSTM-CRF approach to document-level chemical named entity recognition.
Ling LuoZhihao YangPei YangYin ZhangLei WangHongfei LinJian WangPublished in: Bioinform. (2018)
Keyphrases
- named entity recognition
- document level
- conditional random fields
- information extraction
- named entities
- natural language processing
- maximum entropy
- relation extraction
- sentence level
- language model
- semi supervised
- sentiment classification
- text summarization
- probabilistic model
- higher order
- graphical models
- coreference resolution
- hidden markov models
- crf model
- query expansion
- generative model
- text mining
- document retrieval
- machine learning
- pairwise
- information retrieval