{"title":"基于概念图的XML数据建模和查询","authors":"Andrea Éva Molnár, V. Varga, C. Săcărea","doi":"10.23919/SOFTCOM.2017.8115519","DOIUrl":null,"url":null,"abstract":"Conceptual Graphs (CGs) are a knowledge representation language based on the existential graphs of Ch. S. Peirce and the semantic networks of Artificial Intelligence. CGs are also a modeling and design language, which is human readable and computer tractable. This makes CGs suitable for a large variety of applications. The novelty of this paper, is a new approach to XML data modeling based on Conceptual Graphs and a query designer based also on CGs. We underline that the expressive power of Conceptual Graphs helps us to understand, analyze and present the structure of semi-structured data in a form which is also accessible for non-experts.","PeriodicalId":189860,"journal":{"name":"2017 25th International Conference on Software, Telecommunications and Computer Networks (SoftCOM)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Conceptual graphs based modeling and querying of XML data\",\"authors\":\"Andrea Éva Molnár, V. Varga, C. Săcărea\",\"doi\":\"10.23919/SOFTCOM.2017.8115519\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Conceptual Graphs (CGs) are a knowledge representation language based on the existential graphs of Ch. S. Peirce and the semantic networks of Artificial Intelligence. CGs are also a modeling and design language, which is human readable and computer tractable. This makes CGs suitable for a large variety of applications. The novelty of this paper, is a new approach to XML data modeling based on Conceptual Graphs and a query designer based also on CGs. We underline that the expressive power of Conceptual Graphs helps us to understand, analyze and present the structure of semi-structured data in a form which is also accessible for non-experts.\",\"PeriodicalId\":189860,\"journal\":{\"name\":\"2017 25th International Conference on Software, Telecommunications and Computer Networks (SoftCOM)\",\"volume\":\"97 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 25th International Conference on Software, Telecommunications and Computer Networks (SoftCOM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/SOFTCOM.2017.8115519\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 25th International Conference on Software, Telecommunications and Computer Networks (SoftCOM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/SOFTCOM.2017.8115519","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
摘要
概念图(CGs)是基于Ch. S. Peirce的存在图和人工智能语义网络的知识表示语言。cg也是一种建模和设计语言,人类可读,计算机可处理。这使得cg适用于各种各样的应用。本文的新颖之处在于提出了一种基于概念图的XML数据建模的新方法和基于概念图的查询设计器。我们强调,概念图的表达能力有助于我们理解、分析和呈现半结构化数据的结构,这种形式也适用于非专家。
Conceptual graphs based modeling and querying of XML data
Conceptual Graphs (CGs) are a knowledge representation language based on the existential graphs of Ch. S. Peirce and the semantic networks of Artificial Intelligence. CGs are also a modeling and design language, which is human readable and computer tractable. This makes CGs suitable for a large variety of applications. The novelty of this paper, is a new approach to XML data modeling based on Conceptual Graphs and a query designer based also on CGs. We underline that the expressive power of Conceptual Graphs helps us to understand, analyze and present the structure of semi-structured data in a form which is also accessible for non-experts.