基于隐马尔可夫模型的半结构化文本信息抽取研究
Research on Semi Structured Text Information Extraction Based on Hidden Markov Models
蒲治宇1
作者信息
- 1. 中海油信息科技有限公司,广东 深圳 518000
- 折叠
摘要
随着互联网和信息技术的快速发展,大量的文本数据在互联网上被生成和存储,这些文本数据包含了丰富的信息.然而,大部分文本数据都是半结构化的,即数据的组织结构不完整或不规则,不适合直接进行分析和处理.因此,半结构化文本信息抽取成为了一个重要的研究领域,文章基于隐马尔科夫模型对半结构化文本信息的抽取进行研究.
Abstract
With the rapid development of the Internet and information technology,a large amount of text data is generated and stored on the Internet,which contains rich information.However,most text data is semi-structured,meaning that the organizational structure of the data is incomplete or irregular,making it unsuitable for direct analysis and processing.Therefore,semi-structured text information extraction has become an important research field,and this article studies the extraction of semi-structured text information based on hidden Markov models.
关键词
半结构化文本/信息抽取/隐马尔科夫模型Key words
semi-structured text/information extraction/hidden markov model引用本文复制引用
出版年
2024
NETL
NSTL
万方数据