Conception and Linguistic Means of Representation and Knowledge Processing at the Semantic Level

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2023-06-13 DOI:10.3103/S0005105523020073

G. Sergievsky, M. Sergievsky

{"title":"Conception and Linguistic Means of Representation and Knowledge Processing at the Semantic Level","authors":"G. Sergievsky, M. Sergievsky","doi":"10.3103/S0005105523020073","DOIUrl":null,"url":null,"abstract":"<div><div><h3>\n <b>Abstract</b>—</h3><p>The requirements that knowledge representation languages must meet are determined. It is concluded that the reasons for the failures of previous projects within the knowledge-based systems paradigm are the lack of knowledge representation languages focused on processing knowledge expressed in a conceptual form. The main elements of the system are the knowledge base, the database, and the inference machine. Facts are stored in a database in the form of a network of instances of concepts; universal knowledge is presented in the form of an ontology of the domain area, consisting of a set of definitions of concepts, integrity conditions, and rules. The tools of ontology definition allow solving the problem of describing the semantics of concepts using the concept model of the representation/content type, which allows representing and processing information at the semantic level. The advantage of the proposed approach is the possibility of using the same language for entering not only facts and queries but also for defining concepts and rules.</p></div></div>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.3103/S0005105523020073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}

引用次数: 0

Abstract—

The requirements that knowledge representation languages must meet are determined. It is concluded that the reasons for the failures of previous projects within the knowledge-based systems paradigm are the lack of knowledge representation languages focused on processing knowledge expressed in a conceptual form. The main elements of the system are the knowledge base, the database, and the inference machine. Facts are stored in a database in the form of a network of instances of concepts; universal knowledge is presented in the form of an ontology of the domain area, consisting of a set of definitions of concepts, integrity conditions, and rules. The tools of ontology definition allow solving the problem of describing the semantics of concepts using the concept model of the representation/content type, which allows representing and processing information at the semantic level. The advantage of the proposed approach is the possibility of using the same language for entering not only facts and queries but also for defining concepts and rules.

Abstract Image

查看原文本刊更多论文

概念、语言表示方法和语义层面的知识处理

摘要——确定了知识表示语言必须满足的要求。结果表明，以往基于知识的系统范式中的项目失败的原因是缺乏专注于处理以概念形式表达的知识的知识表示语言。系统的主要元素是知识库、数据库和推理机。事实以概念实例网络的形式存储在数据库中；通用知识以领域本体的形式呈现，由概念、完整性条件和规则的一组定义组成。本体定义的工具允许使用表示/内容类型的概念模型来解决描述概念的语义的问题，这允许在语义级别上表示和处理信息。所提出的方法的优点是可以使用相同的语言不仅输入事实和查询，还可以定义概念和规则。

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

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-

自引率

40.00%

发文量

期刊介绍： Automatic Documentation and Mathematical Linguistics is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.