摘要
【目的】从图书信息中快速生成书籍的宣传语。【方法】基于提示学习的思想将爬取的图书信息构造为数据集,使用数据增强、关键词抽取增加信息,最后输入T5 PEGASUS得到基础宣传语。当书评数量达到阈值时加入书评的摘要。【结果】本文模型在数据集上的 Rouge-1、Rouge-2、Rouge-L相较于最优的基线模型分别提升29.0%、37.6%、31.9%,加入书评的摘要能体现用户的兴趣点。【结论】根据图书语料特点设计的实验流程所生成的宣传语具有实际应用价值。
[Objective]This paper aims to quickly generate real-time promotional book summaries and reduce the consumption of workforce and resources.[Methods]First,we constructed a dataset with the crawled book information based on prompt learning.Then,we used data enhancement and keyword extraction to increase information and generated the primary promotion language with the T5 PEGASUS.When the number of book reviews reaches the threshold,the summary of the book reviews will also be added.[Results]Compared with the optimal baseline model,the Rouge-1、Rouge-2、and Rouge-L scores of the proposed model were improved by 29.0%,37.6%,and 31.9%,respectively.Adding the summary of book reviews can reflect the interests of users.[Conclusions]The proposed model could generate summaries based on the characteristics of the book corpus and has practical value.
作者
李岱峰
林凯欣
李栩婷
Li Daifeng;Lin Kaixin;Li Xuting(School of Information Management,Sun Yat-Sen University,Guangzhou 510006,China)
出处
《数据分析与知识发现》
CSSCI
CSCD
北大核心
2023年第3期121-130,共10页
Data Analysis and Knowledge Discovery
基金
广东省科技创新战略专项资金(“攀登计划”专项资金)(项目编号:pdjh2021a0001)的研究成果之一。
