计算机技术与发展2011，Vol.21Issue(5)：115-117,3.
基于HMM/BP混合模型的文本信息抽取研究
Text Information Extraction Research Based on HMM and BP Network Hybrid Model
摘要
Abstract
As a branch of natural language processing, the extraction of useful information in large text , the text information extraction became an important means. Introduce the information extraction widely used two kinds of technical methods: HMM and BP network model, analyze their advantages and disadvantages and on this basis propose a hybrid model, based on two models mentioned above. In this model, the classification by BP network capacity is to make up for deficiencies in the classificationof HMM, HMM through strong time-domain modeling capabilities to make up for weak BP network modeling problem, so the hybrid model has strong modeling capabilities, classified and adaptability ,etc. Experimental results show that compared to the traditional HMM and the BP network model, hybrid model in precision and recall rate is on the increase by 10％ - 15％.关键词
信息抽取/隐马尔可夫模型/BP网络Key words
information extraction/HMM/BPN分类
信息技术与安全科学引用本文复制引用
杨红超,肖基毅..基于HMM/BP混合模型的文本信息抽取研究[J].计算机技术与发展,2011,21(5):115-117,3.基金项目
湖南省科技计划项目(2008GK3090) （2008GK3090）
