Graph search beyond text: Relational searches in semantic hyperlinked data

M. Goldberg, J. Greenman, B. Gutting, M. Magdon-Ismail, J. Schwartz, W. Wallace
{"title":"Graph search beyond text: Relational searches in semantic hyperlinked data","authors":"M. Goldberg, J. Greenman, B. Gutting, M. Magdon-Ismail, J. Schwartz, W. Wallace","doi":"10.1109/ISI.2012.6284276","DOIUrl":null,"url":null,"abstract":"We present novel indexing and searching schemes for semantic graphs based on the notion of the i.degrees of a node. The i.degrees allow searches performed on the graph to use “type” and connection information, rather than textual labels, to identify nodes. We aim to identify a network graph (fragment) within a large semantic graph (database). A fragment may represent incomplete information that a researcher has collected on a sub-network of interest. While textual labels might be available, they are highly unreliable, and cannot be used for identification of hidden networks. Since this problem comes from the classically NP-hard problem of identifying isomorphic subgraphs, our algorithms are heuristic.","PeriodicalId":199734,"journal":{"name":"2012 IEEE International Conference on Intelligence and Security Informatics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Intelligence and Security Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISI.2012.6284276","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

We present novel indexing and searching schemes for semantic graphs based on the notion of the i.degrees of a node. The i.degrees allow searches performed on the graph to use “type” and connection information, rather than textual labels, to identify nodes. We aim to identify a network graph (fragment) within a large semantic graph (database). A fragment may represent incomplete information that a researcher has collected on a sub-network of interest. While textual labels might be available, they are highly unreliable, and cannot be used for identification of hidden networks. Since this problem comes from the classically NP-hard problem of identifying isomorphic subgraphs, our algorithms are heuristic.
超越文本的图形搜索:语义超链接数据中的关系搜索
我们提出了一种基于节点i度概念的语义图索引和搜索方案。i度允许在图上执行的搜索使用“类型”和连接信息,而不是文本标签来识别节点。我们的目标是在一个大型语义图(数据库)中识别一个网络图(片段)。片段可能表示研究人员在感兴趣的子网络上收集的不完整信息。虽然文本标签可能可用,但它们非常不可靠,不能用于识别隐藏网络。由于这个问题来自于识别同构子图的经典np困难问题,因此我们的算法是启发式的。
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:481959085
Book学术官方微信