Queripidia的界面草图:来自Web的查询驱动的知识组合

Laura Dietz, M. Schuhmacher
{"title":"Queripidia的界面草图:来自Web的查询驱动的知识组合","authors":"Laura Dietz, M. Schuhmacher","doi":"10.1145/2810133.2810145","DOIUrl":null,"url":null,"abstract":"We aim to augment textual knowledge resources such as Wikipedia with information from the World Wide Web and at the same time focus on a given information need. We demonstrate a solution based on what we call knowledge portfolios. A knowledge portfolio is a query-specific collection of relevant entities together with associated passages from the Web that explain how the entity is relevant for the query. Knowledge portfolios are extracted through a combination of retrieval from World Wide Web and Wikipedia with a reasoning process on mutual relevance. A key ingredient are entity link annotations that tie abstract entities from the knowledge base into their context on the Web. We demonstrate the results of our fully automated system Queripidia, which is capable to create a knowledge portfolios for any web-style query, on data from the TREC Web track. The online demo is available via http://smart-cactus.org/~dietz/knowport/.","PeriodicalId":298747,"journal":{"name":"Proceedings of the Eighth Workshop on Exploiting Semantic Annotations in Information Retrieval","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"An Interface Sketch for Queripidia: Query-driven Knowledge Portfolios from the Web\",\"authors\":\"Laura Dietz, M. Schuhmacher\",\"doi\":\"10.1145/2810133.2810145\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We aim to augment textual knowledge resources such as Wikipedia with information from the World Wide Web and at the same time focus on a given information need. We demonstrate a solution based on what we call knowledge portfolios. A knowledge portfolio is a query-specific collection of relevant entities together with associated passages from the Web that explain how the entity is relevant for the query. Knowledge portfolios are extracted through a combination of retrieval from World Wide Web and Wikipedia with a reasoning process on mutual relevance. A key ingredient are entity link annotations that tie abstract entities from the knowledge base into their context on the Web. We demonstrate the results of our fully automated system Queripidia, which is capable to create a knowledge portfolios for any web-style query, on data from the TREC Web track. The online demo is available via http://smart-cactus.org/~dietz/knowport/.\",\"PeriodicalId\":298747,\"journal\":{\"name\":\"Proceedings of the Eighth Workshop on Exploiting Semantic Annotations in Information Retrieval\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Eighth Workshop on Exploiting Semantic Annotations in Information Retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2810133.2810145\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Eighth Workshop on Exploiting Semantic Annotations in Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2810133.2810145","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

摘要

我们的目标是增加文本知识资源,如维基百科与来自万维网的信息,同时专注于给定的信息需求。我们展示了一个基于我们称之为知识组合的解决方案。知识组合是特定于查询的相关实体的集合,以及来自Web的相关段落,这些段落解释了实体如何与查询相关。通过对万维网和维基百科的检索,结合相互关联的推理过程,提取知识组合。一个关键因素是实体链接注释,它将知识库中的抽象实体绑定到Web上的上下文中。我们展示了我们的全自动系统Queripidia的结果,它能够在TREC Web track的数据上为任何Web样式的查询创建知识组合。在线演示可通过http://smart-cactus.org/~dietz/knowport/获得。
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
An Interface Sketch for Queripidia: Query-driven Knowledge Portfolios from the Web
We aim to augment textual knowledge resources such as Wikipedia with information from the World Wide Web and at the same time focus on a given information need. We demonstrate a solution based on what we call knowledge portfolios. A knowledge portfolio is a query-specific collection of relevant entities together with associated passages from the Web that explain how the entity is relevant for the query. Knowledge portfolios are extracted through a combination of retrieval from World Wide Web and Wikipedia with a reasoning process on mutual relevance. A key ingredient are entity link annotations that tie abstract entities from the knowledge base into their context on the Web. We demonstrate the results of our fully automated system Queripidia, which is capable to create a knowledge portfolios for any web-style query, on data from the TREC Web track. The online demo is available via http://smart-cactus.org/~dietz/knowport/.
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
Temporal Reconciliation for Dating Photographs Using Entity Information Hugo: Entity-based News Search and Summarisation CADEminer: A System for Mining Consumer Reports on Adverse Drug Side Effects Contextualizing Data on a Content Management System Harnessing Semantics for Answer Sentence Retrieval
×
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