Research on Related Entity Identification Model and Incremental Verification Algorithm for Heterogeneous Networks: Research on Related Entity Identification Model and Incremental Verification Algorithm for Heterogeneous Networks

Q3 Computer Science
Yue Kou, Derong Shen, Heng Liu, Taiming Wang, Tiezheng Nie, Yu Ge
{"title":"Research on Related Entity Identification Model and Incremental Verification Algorithm for Heterogeneous Networks: Research on Related Entity Identification Model and Incremental Verification Algorithm for Heterogeneous Networks","authors":"Yue Kou, Derong Shen, Heng Liu, Taiming Wang, Tiezheng Nie, Yu Ge","doi":"10.3724/SP.J.1016.2013.02096","DOIUrl":null,"url":null,"abstract":"Related entity identification is a necessary technique to find and integrate the entities that are related tightly in heterogeneous networks.It is useful to make users understand the search result better.However,current techniques consider limited influence factors for related entity identification and lack verification which often lead to dumb results.In this paper,we present a two-phase related entity identification model by fully considering entity schema and entity feature.Also an incremental verification algorithm is proposed to iteratively verify and repair the result of identification.The experiments demonstrate the feasibility and effectiveness of our key techniques.","PeriodicalId":35776,"journal":{"name":"计算机学报","volume":"36 1","pages":"2096-2108"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"计算机学报","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.3724/SP.J.1016.2013.02096","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 1

Abstract

Related entity identification is a necessary technique to find and integrate the entities that are related tightly in heterogeneous networks.It is useful to make users understand the search result better.However,current techniques consider limited influence factors for related entity identification and lack verification which often lead to dumb results.In this paper,we present a two-phase related entity identification model by fully considering entity schema and entity feature.Also an incremental verification algorithm is proposed to iteratively verify and repair the result of identification.The experiments demonstrate the feasibility and effectiveness of our key techniques.
异构网络相关实体识别模型及增量验证算法研究异构网络相关实体识别模型及增量验证算法研究
关联实体识别是发现和整合异构网络中紧密关联实体的必要技术。让用户更好地理解搜索结果是很有用的。然而,目前的技术对相关实体识别考虑的影响因素有限,缺乏验证,往往导致结果模糊。本文在充分考虑实体模式和实体特征的基础上,提出了一种两阶段相关的实体识别模型。提出了一种增量验证算法,对识别结果进行迭代验证和修复。实验验证了关键技术的可行性和有效性。
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
计算机学报
计算机学报 Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
3.00
自引率
0.00%
发文量
7308
期刊介绍:
×
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