文本语义表征技术研究综述  

Review of text semantic representation technology

作　　者：赵小娟 ZHAO Xiaojuan(Luoyang Open University,Luoyang 471000,China)

机构地区：[1]洛阳开放大学,河南洛阳471000

出　　处：《无线互联科技》2024年第12期112-114,共3页Wireless Internet Technology

摘　　要：文本语义表征是自然语言处理领域的核心任务之一,将文本信息转化为计算机可理解的数值表示能够实现对文本深层含义的挖掘和应用。文章通过对传统文本语义表征方法的梳理,剖析了这些方法的优势与局限,并重点探讨了深度学习在文本语义表征领域的突破性进展和发展趋势,旨在全面综述文本语义表征技术的研究现状与发展趋势,为相关领域的研究提供有益的参考和启示。Text semantic representation is one of the core tasks in the field of natural language processing,which transforms text information into a numerical representation that can be understood by computers,so as to realize the mining and application of the deep meaning of text.This article reviews the traditional methods of text semantic representation,analyzes their advantages and limitations,and focuses on the breakthroughs and development trends of deep learning in the field of text semantic representation.The aim is to provide a comprehensive overview of the research status and development trends of text semantic representation technology,and to provide useful references and insights for research in related fields.

关 键 词：文本语义表征 词嵌入 深度学习模型 语义向量 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]