利用知识图谱进行开放领域问答

J. Costa, Anagha Kulkarni
{"title":"利用知识图谱进行开放领域问答","authors":"J. Costa, Anagha Kulkarni","doi":"10.1109/WI.2018.00-63","DOIUrl":null,"url":null,"abstract":"Rich and comprehensive knowledge graphs (KG) of the Web, such as, Google KG, NELL, and Diffbot KG, are becoming increasingly prevalent and powerful as the underlying AI technology is rapidly progressing. In this work, we leverage this ongoing advancement for the task of answering questions posed from any domain and any type (factoid and non-factoid). We present a framework for knowledge graph based question answering systems, KGQA, and experiment with an instance of this framework that employs Diffbot KG. The unique features offered by KGs, such as, rapid query response time, connections between related graph objects, and structured information, are used to design a QA system that is effective and efficient.","PeriodicalId":405966,"journal":{"name":"2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Leveraging Knowledge Graph for Open-Domain Question Answering\",\"authors\":\"J. Costa, Anagha Kulkarni\",\"doi\":\"10.1109/WI.2018.00-63\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Rich and comprehensive knowledge graphs (KG) of the Web, such as, Google KG, NELL, and Diffbot KG, are becoming increasingly prevalent and powerful as the underlying AI technology is rapidly progressing. In this work, we leverage this ongoing advancement for the task of answering questions posed from any domain and any type (factoid and non-factoid). We present a framework for knowledge graph based question answering systems, KGQA, and experiment with an instance of this framework that employs Diffbot KG. The unique features offered by KGs, such as, rapid query response time, connections between related graph objects, and structured information, are used to design a QA system that is effective and efficient.\",\"PeriodicalId\":405966,\"journal\":{\"name\":\"2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)\",\"volume\":\"118 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WI.2018.00-63\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI.2018.00-63","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

随着底层人工智能技术的快速发展,丰富而全面的Web知识图(KG),如谷歌KG、NELL、Diffbot KG等,正变得越来越普遍和强大。在这项工作中,我们利用这一正在进行的进步来回答来自任何领域和任何类型(事实和非事实)的问题。我们提出了一个基于知识图谱的问答系统框架,KGQA,并使用Diffbot KG对该框架的一个实例进行了实验。KGs提供的独特功能,如快速的查询响应时间、相关图形对象之间的连接和结构化信息,被用来设计一个有效和高效的QA系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leveraging Knowledge Graph for Open-Domain Question Answering
Rich and comprehensive knowledge graphs (KG) of the Web, such as, Google KG, NELL, and Diffbot KG, are becoming increasingly prevalent and powerful as the underlying AI technology is rapidly progressing. In this work, we leverage this ongoing advancement for the task of answering questions posed from any domain and any type (factoid and non-factoid). We present a framework for knowledge graph based question answering systems, KGQA, and experiment with an instance of this framework that employs Diffbot KG. The unique features offered by KGs, such as, rapid query response time, connections between related graph objects, and structured information, are used to design a QA system that is effective and efficient.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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