朝向一个开放的问题回答架构

Edgard Marx, Ricardo Usbeck, A. N. Ngomo, Konrad Höffner, Jens Lehmann, S. Auer
{"title":"朝向一个开放的问题回答架构","authors":"Edgard Marx, Ricardo Usbeck, A. N. Ngomo, Konrad Höffner, Jens Lehmann, S. Auer","doi":"10.1145/2660517.2660519","DOIUrl":null,"url":null,"abstract":"Billions of facts pertaining to a multitude of domains are now available on the Web as RDF data. However, accessing this data is still a difficult endeavour for non-expert users. In order to meliorate the access to this data, approaches imposing minimal hurdles to their users are required. Although many question answering systems over Linked Data have being proposed, retrieving the desired data is still significantly challenging. In addition, developing and evaluating question answering systems remains a very complex task. To overcome these obstacles, we present a modular and extensible open-source question answering framework. We demonstrate how the framework can be used by integrating two state-of-the-art question answering systems. As a result our evaluation shows that overall better results can be achieved by the use of combination rather than individual stand-alone versions.","PeriodicalId":344435,"journal":{"name":"Joint Conference on Lexical and Computational Semantics","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"53","resultStr":"{\"title\":\"Towards an open question answering architecture\",\"authors\":\"Edgard Marx, Ricardo Usbeck, A. N. Ngomo, Konrad Höffner, Jens Lehmann, S. Auer\",\"doi\":\"10.1145/2660517.2660519\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Billions of facts pertaining to a multitude of domains are now available on the Web as RDF data. However, accessing this data is still a difficult endeavour for non-expert users. In order to meliorate the access to this data, approaches imposing minimal hurdles to their users are required. Although many question answering systems over Linked Data have being proposed, retrieving the desired data is still significantly challenging. In addition, developing and evaluating question answering systems remains a very complex task. To overcome these obstacles, we present a modular and extensible open-source question answering framework. We demonstrate how the framework can be used by integrating two state-of-the-art question answering systems. As a result our evaluation shows that overall better results can be achieved by the use of combination rather than individual stand-alone versions.\",\"PeriodicalId\":344435,\"journal\":{\"name\":\"Joint Conference on Lexical and Computational Semantics\",\"volume\":\"2014 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"53\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Joint Conference on Lexical and Computational Semantics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2660517.2660519\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Joint Conference on Lexical and Computational Semantics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2660517.2660519","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 53

摘要

与众多领域相关的数十亿事实现在都以RDF数据的形式出现在Web上。然而,对于非专业用户来说,访问这些数据仍然是一项困难的努力。为了改善对这些数据的访问,需要对其用户施加最小障碍的方法。尽管已经提出了许多基于关联数据的问答系统,但检索所需数据仍然具有很大的挑战性。此外,开发和评估问答系统仍然是一项非常复杂的任务。为了克服这些障碍,我们提出了一个模块化和可扩展的开源问答框架。我们将演示如何通过集成两个最先进的问答系统来使用该框架。因此,我们的评估表明,使用组合而不是单独的单独版本可以获得更好的总体结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Towards an open question answering architecture
Billions of facts pertaining to a multitude of domains are now available on the Web as RDF data. However, accessing this data is still a difficult endeavour for non-expert users. In order to meliorate the access to this data, approaches imposing minimal hurdles to their users are required. Although many question answering systems over Linked Data have being proposed, retrieving the desired data is still significantly challenging. In addition, developing and evaluating question answering systems remains a very complex task. To overcome these obstacles, we present a modular and extensible open-source question answering framework. We demonstrate how the framework can be used by integrating two state-of-the-art question answering systems. As a result our evaluation shows that overall better results can be achieved by the use of combination rather than individual stand-alone versions.
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
期刊最新文献
Embedded Semantic Lexicon Induction with Joint Global and Local Optimization Semantic Frames and Visual Scenes: Learning Semantic Role Inventories from Image and Video Descriptions Comparing Approaches for Automatic Question Identification Detecting Asymmetric Semantic Relations in Context: A Case-Study on Hypernymy Detection Deep Learning Models For Multiword Expression Identification
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1