基于OWL的时空知识图表示的一般表征

Lin Zhu, Luyi Bai, Xuesong Hao, Hongji Yang
{"title":"基于OWL的时空知识图表示的一般表征","authors":"Lin Zhu, Luyi Bai, Xuesong Hao, Hongji Yang","doi":"10.1109/QRS-C57518.2022.00108","DOIUrl":null,"url":null,"abstract":"Knowledge graph is used to represent the concepts, entities and relationships existing in the real world, which can be applied to many applications such as creative computing and recommendation system. Structurally, knowledge graph includes data layer and schema layer. Spatiotemporal knowledge graph extends the common knowledge graph to a certain extent, which is mainly reflected in the entity layer (data layer). Spatiotemporal knowledge graph includes temporal feature, spatial feature and spatiotemporal feature. In the pattern layer, spatiotemporal knowledge graph mainly adds concepts and relationships between concepts, which needs to be re-modeled. In this paper, as a spatiotemporal extension of the general description logic based on OWL logic, the spatiotemporal description logic (ST DL) is proposed to describe the spatiotemporal knowledge graph, and ST OWL is extended from three aspects: OWL class description, OWL axiom and OWL data type. Then, the corresponding transformation rules are proposed, and the instance is transformed from spatiotemporal ontology structure to spatiotemporal knowledge graph.","PeriodicalId":183728,"journal":{"name":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A General Characterization of Representing Spatiotemporal Knowledge Graph based on OWL\",\"authors\":\"Lin Zhu, Luyi Bai, Xuesong Hao, Hongji Yang\",\"doi\":\"10.1109/QRS-C57518.2022.00108\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Knowledge graph is used to represent the concepts, entities and relationships existing in the real world, which can be applied to many applications such as creative computing and recommendation system. Structurally, knowledge graph includes data layer and schema layer. Spatiotemporal knowledge graph extends the common knowledge graph to a certain extent, which is mainly reflected in the entity layer (data layer). Spatiotemporal knowledge graph includes temporal feature, spatial feature and spatiotemporal feature. In the pattern layer, spatiotemporal knowledge graph mainly adds concepts and relationships between concepts, which needs to be re-modeled. In this paper, as a spatiotemporal extension of the general description logic based on OWL logic, the spatiotemporal description logic (ST DL) is proposed to describe the spatiotemporal knowledge graph, and ST OWL is extended from three aspects: OWL class description, OWL axiom and OWL data type. Then, the corresponding transformation rules are proposed, and the instance is transformed from spatiotemporal ontology structure to spatiotemporal knowledge graph.\",\"PeriodicalId\":183728,\"journal\":{\"name\":\"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/QRS-C57518.2022.00108\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 22nd International Conference on Software Quality, Reliability, and Security Companion (QRS-C)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QRS-C57518.2022.00108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

知识图谱用于表示现实世界中存在的概念、实体和关系,可以应用于创意计算和推荐系统等许多应用。知识图谱在结构上包括数据层和模式层。时空知识图谱在一定程度上扩展了普通知识图谱,这主要体现在实体层(数据层)。时空知识图谱包括时间特征、空间特征和时空特征。在模式层,时空知识图主要添加概念和概念间的关系,需要对其进行重新建模。本文在OWL逻辑的基础上,提出了时空描述逻辑(ST DL)作为一般描述逻辑的时空扩展,从OWL类描述、OWL公理和OWL数据类型三个方面对时空知识图进行了扩展。然后,提出相应的转换规则,将实例从时空本体结构转换为时空知识图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A General Characterization of Representing Spatiotemporal Knowledge Graph based on OWL
Knowledge graph is used to represent the concepts, entities and relationships existing in the real world, which can be applied to many applications such as creative computing and recommendation system. Structurally, knowledge graph includes data layer and schema layer. Spatiotemporal knowledge graph extends the common knowledge graph to a certain extent, which is mainly reflected in the entity layer (data layer). Spatiotemporal knowledge graph includes temporal feature, spatial feature and spatiotemporal feature. In the pattern layer, spatiotemporal knowledge graph mainly adds concepts and relationships between concepts, which needs to be re-modeled. In this paper, as a spatiotemporal extension of the general description logic based on OWL logic, the spatiotemporal description logic (ST DL) is proposed to describe the spatiotemporal knowledge graph, and ST OWL is extended from three aspects: OWL class description, OWL axiom and OWL data type. Then, the corresponding transformation rules are proposed, and the instance is transformed from spatiotemporal ontology structure to spatiotemporal knowledge graph.
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
×
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