Learning to Define Terms in the Software Domain

NUT@EMNLP Pub Date : 2018-11-01 DOI:10.18653/v1/W18-6122
Vidhisha Balachandran, Dheeraj Rajagopal, R. Catherine, William W. Cohen
{"title":"Learning to Define Terms in the Software Domain","authors":"Vidhisha Balachandran, Dheeraj Rajagopal, R. Catherine, William W. Cohen","doi":"10.18653/v1/W18-6122","DOIUrl":null,"url":null,"abstract":"One way to test a person’s knowledge of a domain is to ask them to define domain-specific terms. Here, we investigate the task of automatically generating definitions of technical terms by reading text from the technical domain. Specifically, we learn definitions of software entities from a large corpus built from the user forum Stack Overflow. To model definitions, we train a language model and incorporate additional domain-specific information like word co-occurrence, and ontological category information. Our approach improves previous baselines by 2 BLEU points for the definition generation task. Our experiments also show the additional challenges associated with the task and the short-comings of language-model based architectures for definition generation.","PeriodicalId":207795,"journal":{"name":"NUT@EMNLP","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NUT@EMNLP","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18653/v1/W18-6122","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

One way to test a person’s knowledge of a domain is to ask them to define domain-specific terms. Here, we investigate the task of automatically generating definitions of technical terms by reading text from the technical domain. Specifically, we learn definitions of software entities from a large corpus built from the user forum Stack Overflow. To model definitions, we train a language model and incorporate additional domain-specific information like word co-occurrence, and ontological category information. Our approach improves previous baselines by 2 BLEU points for the definition generation task. Our experiments also show the additional challenges associated with the task and the short-comings of language-model based architectures for definition generation.
学习在软件领域定义术语
测试一个人对领域知识的一种方法是让他们定义特定于领域的术语。在这里,我们研究了通过从技术领域读取文本来自动生成技术术语定义的任务。具体来说,我们从用户论坛Stack Overflow构建的大型语料库中学习软件实体的定义。为了建模定义,我们训练了一个语言模型,并结合了额外的领域特定信息,如词共现和本体类别信息。对于定义生成任务,我们的方法将之前的基线提高了2个BLEU点。我们的实验还显示了与该任务相关的额外挑战以及用于定义生成的基于语言模型的体系结构的缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信