End-to-end sequence labeling via deep learning for automatic extraction of agricultural regulations.
Borja Espejo-GarcíaFrancisco J. López-PellicerJavier LacastaRamon Piedrafita MorenoF. Javier Zarazaga-SoriaPublished in: Comput. Electron. Agric. (2019)
Keyphrases
- deep learning
- automatic extraction
- end to end
- sequence labeling
- conditional random fields
- dependency parsing
- relation extraction
- named entity recognition
- weakly supervised
- unsupervised learning
- machine learning
- structured prediction
- mental models
- named entities
- information extraction
- natural language processing
- graphical models
- information retrieval
- pairwise
- text classification
- semi supervised
- maximum entropy
- active learning
- active contours
- natural language
- hidden markov models