Entity-relationship queries over wikipedia

SMUC '10 Pub Date : 2010-10-30 DOI:10.1145/1871985.1871991
Xiaonan Li, Chengkai Li, Cong Yu
{"title":"Entity-relationship queries over wikipedia","authors":"Xiaonan Li, Chengkai Li, Cong Yu","doi":"10.1145/1871985.1871991","DOIUrl":null,"url":null,"abstract":"Wikipedia is the largest user-generated knowledge base. We propose a structured query mechanism, entity-relationship query, for searching entities in Wikipedia corpus by their properties and inter-relationships. An entity-relationship query consists of arbitrary number of predicates on desired entities. The semantics of each predicate is specified with keywords. Entity-relationship query searches entities directly over text rather than pre-extracted structured data stores. This characteristic brings two benefits: (1) Query semantics can be intuitively expressed by keywords; (2) It avoids information loss that happens during extraction. We present a ranking framework for general entity-relationship queries and a position-based Bounded Cumulative Model for accurate ranking of query answers. Experiments on INEX benchmark queries and our own crafted queries show the effectiveness and accuracy of our ranking method.","PeriodicalId":244822,"journal":{"name":"SMUC '10","volume":"95 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SMUC '10","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1871985.1871991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23

Abstract

Wikipedia is the largest user-generated knowledge base. We propose a structured query mechanism, entity-relationship query, for searching entities in Wikipedia corpus by their properties and inter-relationships. An entity-relationship query consists of arbitrary number of predicates on desired entities. The semantics of each predicate is specified with keywords. Entity-relationship query searches entities directly over text rather than pre-extracted structured data stores. This characteristic brings two benefits: (1) Query semantics can be intuitively expressed by keywords; (2) It avoids information loss that happens during extraction. We present a ranking framework for general entity-relationship queries and a position-based Bounded Cumulative Model for accurate ranking of query answers. Experiments on INEX benchmark queries and our own crafted queries show the effectiveness and accuracy of our ranking method.
维基百科上的实体关系查询
维基百科是最大的用户生成知识库。针对维基百科语料库中实体的属性和相互关系,提出了一种结构化查询机制——实体-关系查询。实体-关系查询由所需实体上任意数量的谓词组成。每个谓词的语义都用关键字指定。实体关系查询直接在文本上搜索实体,而不是预先提取的结构化数据存储。这个特性带来了两个好处:(1)查询语义可以直观地用关键字表示;(2)避免了提取过程中信息的丢失。我们提出了一个用于一般实体关系查询的排序框架和一个用于查询答案精确排序的基于位置的有界累积模型。在INEX基准查询和我们自己制作的查询上的实验表明了我们的排名方法的有效性和准确性。
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