基于CRFs和语块分析的中文未登录术语识别研究

Research on Out-of-vocabulary Term Recognition Based on CRFs and Chunking

针对目前未登录术语识别的研究现状,提出了基于CRFs和语块分析的中文未登录术语识别模型,并制作了专利文本语料进行实验验证,实验结果表明该模型在识别中文未登录术语中的表现是有效的,后期有待构建更加专业的语料库来进一步提高识别结果。

In view of the current research of the Chinese out-of-vocabulary term recognition, this paper present a model of term recognition based on CRFs and Chunking, and then make a series of corpus on patent text to test and verify the model. The result shows that the model is valid to recognize the out-of- vocabulary term, but the result should be improved in the future though make a more professional corpus.