A comparison of conditional random fields and structured support vector machines for chemical entity recognition in biomedical literature.
Buzhou TangYudong FengXiaolong WangYonghui WuYaoyun ZhangMin JiangJingqi WangHua XuPublished in: J. Cheminformatics (2015)
Keyphrases
- conditional random fields
- biomedical literature
- structured learning
- support vector
- text mining
- information extraction
- graphical models
- probabilistic model
- hidden markov models
- higher order
- markov random field
- sequence labeling
- automatic extraction
- generative model
- pairwise
- protein protein interactions
- named entity recognition
- maximum margin
- structured prediction
- web page prediction
- machine learning
- real world
- segmentation method
- feature selection
- information retrieval
- text documents
- binary classification
- parameter estimation
- semantic relationships
- text classification
- co occurrence