A Knowledge Graph Exploration Method with No Prior Knowledge

Ariani Indrawati, Zaenal Akbar, D. Rini, Aris Yaman, Y. Kartika, D. R. Saleh
{"title":"A Knowledge Graph Exploration Method with No Prior Knowledge","authors":"Ariani Indrawati, Zaenal Akbar, D. Rini, Aris Yaman, Y. Kartika, D. R. Saleh","doi":"10.1145/3575882.3575918","DOIUrl":null,"url":null,"abstract":"Various sectors now widely adopt knowledge graphs to describe and share their organizational knowledge bases. Unfortunately, the majority of knowledge-sharing systems are designed for domain experts. Making it extremely difficult for a non-expert to understand the content and explore the graph. A solution to this issue is using a machine-assisted knowledge graph exploration approach. This research introduces a knowledge exploration method to systematically and efficiently navigate a knowledge graph. First, we modeled the knowledge graphs based on the existing common schema. Second, we created a search tree technique to navigate the knowledge graph efficiently. The algorithm solves the problem by determining the path of knowledge graph exploration. We evaluated the method using a knowledge base of morphological characteristics of Capsicum. The goal of graph exploration was to identify a Capsicum species correctly. As a result, the proposed mechanism can achieve high precision, even when the search’s starting point is unknown beforehand.","PeriodicalId":367340,"journal":{"name":"Proceedings of the 2022 International Conference on Computer, Control, Informatics and Its Applications","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2022 International Conference on Computer, Control, Informatics and Its Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3575882.3575918","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

Various sectors now widely adopt knowledge graphs to describe and share their organizational knowledge bases. Unfortunately, the majority of knowledge-sharing systems are designed for domain experts. Making it extremely difficult for a non-expert to understand the content and explore the graph. A solution to this issue is using a machine-assisted knowledge graph exploration approach. This research introduces a knowledge exploration method to systematically and efficiently navigate a knowledge graph. First, we modeled the knowledge graphs based on the existing common schema. Second, we created a search tree technique to navigate the knowledge graph efficiently. The algorithm solves the problem by determining the path of knowledge graph exploration. We evaluated the method using a knowledge base of morphological characteristics of Capsicum. The goal of graph exploration was to identify a Capsicum species correctly. As a result, the proposed mechanism can achieve high precision, even when the search’s starting point is unknown beforehand.
一种无先验知识的知识图探索方法
各个部门现在广泛采用知识图来描述和共享其组织知识库。不幸的是,大多数知识共享系统都是为领域专家设计的。让非专业人士很难理解内容和探索图表。解决这个问题的方法是使用机器辅助知识图探索方法。本文介绍了一种知识探索方法,用于系统、高效地导航知识图谱。首先,我们基于现有的通用模式对知识图进行建模。其次,我们创建了一种搜索树技术来有效地导航知识图谱。该算法通过确定知识图探索路径来解决这一问题。我们利用辣椒的形态特征知识库来评估这种方法。图探索的目标是正确识别辣椒品种。因此,即使在搜索的起始点事先未知的情况下,所提出的机制也能达到较高的精度。
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