A Survey on Machine Learning Techniques to Extract Chemical Names from Text Documents
نویسنده
چکیده
The chemical name extraction has a great importance in the biomedical field. Named Entity Recognition is the subtask of information extraction that is used to identify named entities in the given data. There are various dictionary-based, rule-based and machine learning approaches available for Named Entity Recognition. Rule based techniques include hand written rules. In this paper an extensive survey of machine learning models such as Hidden Markov Model (HMM), Support Vector Machine (SVM), Conditional Random Fields (CRFs) etc. that are used to develop NER systems is carried out. Keywords— Chemical name extraction, Named Entity, Hidden markov model, Conditional random fields, Feature functions, Support vector machine.
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