摘要
水利水电工程专业文本信息处理与分析以往主要依赖于人工交互,存在过程繁琐、效率低且易出错等问题。本文基于自然语言处理技术,引入Attention机制对Word2vec技术加以改进,提出了一种智能高效的水利水电工程专业词识别提取与分析方法。该方法通过组合Attention机制,改进Word2vec技术建立了专业词向量计算模型;根据所求词向量,计算词语间相似度,以词语间相似度为组合标准,组合提取水利水电工程专业词;进而结合已有的水利水电工程专业文本,验证所提取专业词的可信度,实现了水利水电工程专业词的自动提炼,构建了一套水利水电工程专业词智能识别提取与分析体系。该方法应用于实际某混凝土大坝长达229周的施工监理周报文本分析中,经过3轮识别计算与分析,获得了9034个水利水电工程专业词,准确率为87.58%,有效提升了水利水电工程专业文本信息提取分析的效率、准确率与智能化水平。
The traditional text information processing and analysis of hydraulic engineering mainly rely on manual interaction,which exists some problems such as complicated processes,low efficiency,error-prone and so on.In this study,an intelligent and high-efficiency method of professional technical word recogni⁃tion extraction and analysis is proposed for hydraulic engineering based on the Natural Language Processing(NLP)technology,integrating the Word2vec technique with the attention mechanism.The word vector com⁃puting model by the improved Word2vec technology is established.The word vector is used to calculate the similarity between words.The similarity between words serves as a combination standard to extract profes⁃sional technical words of hydraulic engineering.An intelligent recognition and analysis framework for profes⁃sional technical words of hydraulic project management is established by professional texts to verify the cred⁃ibility and realize the automatic extraction accuracy of professional technical words.This approach is ap⁃plied to analyze the weekly supervision report text of a practical concrete dam construction for 229 weeks.There are 9034 extracted professional technical words after three iterations,and the accuracy is 87.58%.It effectively improves the efficiency,accuracy and intelligence level of text information extraction and analy⁃sis of hydraulic engineering.
作者
李明超
田丹
沈扬
Jonathan Shi
韩帅
LI Mingchao;TIAN Dan;SHEN Yang;Jonathan Shi;HAN Shuai(State Key Laboratory of Hydraulic Engineering Simulation and Safety,Tianjin University,Tianjin 300350,China;China Three Gorges Corporation,Beijing 100038,China;College of Engineering,Louisiana State University,Baton Rouge,LA 70803,USA)
出处
《水利学报》
EI
CSCD
北大核心
2020年第7期816-826,共11页
Journal of Hydraulic Engineering
基金
国家自然科学基金项目(51879185)
国家重点研发计划项目(2018YFC0406905)
国家优秀青年科学基金项目(51622904)。
