Academic
Publications
Named Entity Recognition from Biomedical Text Using SVM

Named Entity Recognition from Biomedical Text Using SVM,10.1109/icbbe.2011.5779984,Zhenfei Ju,Jian Wang,Fei Zhu

Named Entity Recognition from Biomedical Text Using SVM  
BibTex | RIS | RefWorks Download
Nowadays biomedical research is developing rapidly. A large number of biomedical knowledge exists in the form of unstructured text documents in various files. Named Entity Recognition (NER) from biomedical text is one of the basic task s of biomedical text mining, of which purpose is to recognize the name of the specified type from the collection of biomedical text. NER result is usually the processing object of other text mining. NER from biological text is the foundation of bioinformatics research. At present, the best f-measure of biological named entity recognition system has reached more than 80%, but is lower than general NER system which can reach about 90%. Here we use support vector machine (SVM), which is an effective and efficient tool to analyze data and recognize patterns, to recognize biomedical named entity. We get data set from GENIA corpus which is a collection of Medline abstracts. In the experiment, we get precision rate= 84.24% and recall rate=80.76% finally.
Cumulative Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.