CAJ | 학술논문

自然语言处理技术是计算机科学领域与人工智能领域中的一个重要方向，其中信息抽取是近年来新兴起的一个研究领域。由于汉语自身结构松散、语法语义灵活等特点，使得中文文本中信息抽取具有较大的难度。本文提出句法分析和隐马尔科夫模型相结合的事件属性抽取方法，其主要思想是先利用句法分析对中文文本进行分析，将得到的句法结构交给隐马尔科夫模型进行学习得到一个抽取模型，然后再由此模型对中文文本进行抽取。实验表明，该方法具有较高的准确率和召回率。
자연어언처리기술시계산궤과학영역여인공지능영역중적일개중요방향，기중신식추취시근년래신흥기적일개연구영역。유우한어자신결구송산、어법어의령활등특점，사득중문문본중신식추취구유교대적난도。본문제출구법분석화은마이과부모형상결합적사건속성추취방법，기주요사상시선이용구법분석대중문문본진행분석，장득도적구법결구교급은마이과부모형진행학습득도일개추취모형，연후재유차모형대중문문본진행추취。실험표명，해방법구유교고적준학솔화소회솔。
Natural language processing technology is an important direction in the field of computer science and artificial intelligence,and the Chinese text information extraction is a new rising researching field in recent years. Due to the character of the loose structure of Chinese text,the flexibility of grammar and semanteme,the research of Chinese natural language processing has a difficult challenge nowadays. In the paper, a method of the combine of syntactic and HMM (Hidden Markov Model) was proposed. The main idea is to use syntax to analyze the Chinese text,then submit the syntactic structure to HMM and get a HMM model through learning it,finally the event properties can be extracted by the HMM model. The experiment shows that the method has higher precision and recall than normal algorithm.