计算机与现代化 ›› 2022, Vol. 0 ›› Issue (06): 56-66.
出版日期:
2022-06-23
发布日期:
2022-06-23
作者简介:
张紫芸(1995—),女,陕西宝鸡人,硕士研究生,研究方向:算法设计与分析,E-mail: 1048735602@qq.com; 王文发(1968—),男,陕西志丹人,教授,硕士生导师,研究方向:算法分析与设计,E-mail: wwf@13010360; 通信作者:马乐荣(1974—),男,陕西神木人,教授,硕士生导师,博士,研究方向:自然语言处理,E-mail: mlr@yau.edu.cn; 丁苍峰(1978—),男,河南唐河人,副教授,博士,研究方向:自然语言处理,E-mail: dcf@yau.edu.cn。
基金资助:
Online:
2022-06-23
Published:
2022-06-23
摘要: 随着互联网产生的文本数据越来越多,文本信息过载问题日益严重,对各类文本进行一个“降维”处理显得非常必要,文本摘要便是其中一个重要的手段,也是人工智能领域研究的热点和难点之一。文本摘要旨在将文本或文本集合转换为包含关键信息的简短摘要。近年来语言模型的预处理提高了许多自然语言处理任务的技术水平,包括情感分析、问答、自然语言推理、命名实体识别和文本相似性、文本摘要。本文梳理文本摘要以往的经典方法和近几年的基于预训练的文本摘要方法,并对文本摘要的数据集以及评价方法进行整理,最后总结文本摘要目前面临的挑战与发展趋势。
张紫芸, 王文发, 马乐荣, 丁苍峰. 文本摘要模型的研究进展[J]. 计算机与现代化, 2022, 0(06): 56-66.
ZHANG Zi-yun, WANG Wen-fa, MA Le-rong, DING Cang-feng. Research Progress of Text Summarization Model[J]. Computer and Modernization, 2022, 0(06): 56-66.
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