BIOMEDICAL NAMED ENTITY RECOGNITION USING SECOND-ORDER CONDITIONAL RANDOM FIELDS

摘要：

Biomedical named entity recognition (NER) is an important technique for biological information extraction.Here, we have proposed a model using machine learning where biological terms are recognized using second-order conditional random fields (CRFs).From our experiments with the JNLPBA 2004 dataset, the CRFs labeling model returns an Fscore prediction value of almost 99％.

关键词： Biological Information Extraction Conditional Random Fields Biological Named Entity Recognition

作者: SUPATTANAWAREE THIPCHAROEN SITTHICHOKE SUBPAIBOONKIT JEERAYUT CHAIJARUWANICH

作者单位: Bioinformatics Research Laboratory,Department of Computer Science,Faculty of Science,Chiang Mai University,Thailand

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer Technology and Development(2011第三届计算机技术与发展国际会议 ICCTD2011)

会议地点: 成都

会议语种:英文

页码: 1212-1216

在线出版日期: 2011-11-25（万方平台首次上网日期，不代表论文的发表时间）