CAJ | 학술논문

随着因特网技术的迅速发展,网上信息成几何级数增长,如何从这些海量联机非结构化文本中自动抽取出结构化信息成为目前重要的研究课题.研究了基于隐马尔可夫模型的Web信息抽取算法,着重探讨了隐马尔可夫模型在文本信息抽取中应该如何应用,数据应该如何标记,并对隐马尔可夫模型在文本信息抽取中的应用提出了几个改进的方法,建立了基于HMM的Web信息抽取模型,并对信息抽取后的数据进行了分析对比,验证了改进算法的有效性.
수착인특망기술적신속발전,망상신식성궤하급수증장,여하종저사해량련궤비결구화문본중자동추취출결구화신식성위목전중요적연구과제.연구료기우은마이가부모형적Web신식추취산법,착중탐토료은마이가부모형재문본신식추취중응해여하응용,수거응해여하표기,병대은마이가부모형재문본신식추취중적응용제출료궤개개진적방법,건립료기우HMM적Web신식추취모형,병대신식추취후적수거진행료분석대비,험증료개진산법적유효성.
With the development of the Internet technologies.the information on the Internet increases exponentially.One important research focuses on how to extract structured data from these great capacities of online documents in unstructured texts.This thesis mainly studied relative algorithms on Web information extraction based on hidden Markov model(HMM).discussed hoW to use HMM and how to mark data in text information extraction,Offered several methods to improve the hidden Markov model in information extraction,introduced the establishment of Web information extraction model based on HMM,Comparatively analysed the output data of information extraction,verified the validity of the algorithm through experiments.