Main Article Content
The Named Entity Recognition refers to identification of text from given samples and is most important & fundamental task in biomedical terms extraction. This field is very challenging in recent years. Its aim is to extract and classify the biomedical text terms like proteins, genes, DNA, RNA etc. which, in general, have complex structures and are difficult to recognize. This paper briefly defines Biomedical Named Entity Recognition. In this, the various methods for feature detection & classification like SVM, Neural Networks & K-nearest neighbour and along with various previous works has been discussed. Different NER features in context to identification and classification of named entities have also been reviewed. In which SVM function is used to increase efficiency of biomedical terms extraction process.
Keywords: BioNER, SVM,K-Nearest Neigbour, Neural Network, F-Score.
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