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基于在线谣言的内容特征的域本体结构研究

Jianbo Zhao¹, Huailiang Liu², Weili Zhang²

¹School of Economics and Management, Xidian University, 266 Xifeng Road, Xi'an, 710071, China. zhaojianbo@stu.xidian.edu.cn.

Scientific reports

|May 27, 2024

概括

这项研究引入了一种用于分析在线谣言的新型本体结构方法. 它使语义解析和推理能够改善谣言检测和治理.

科学领域:

计算机科学计算机科学
信息科学信息科学信息科学
人工智能的人工智能

背景情况:

在线谣言由于其普遍性和难以识别而造成重大社会和个人伤害.
有效的谣言检测和治理需要对谣言内容特征进行深入的语义分析.

研究的目的:

为在线谣言文本的语义解析和推理提出一个域本体结构方法.
提高对谣言内容的理解和分类.

主要方法:

从术语,框架和实例层构建谣言域本体,重复使用顶级本体,并从文献和实体中提取特征.
核心类 (5个母类,88个子类) 和概念层次的定义,以及实体关系的对象和数据属性.
在OWL中编码本体,使用Protégé进行可视化,并使用SWRL规则和Pellet推理器进行知识挖掘/验证.

主要成果:

开发一个谣言领域的本体学,具有定义的概念层次和属性.
成功地应用了OWL,Protégé,SWRL和Pellet推理器来进行本体学编码,可视化和知识验证.
创建一个基于真实谣言数据集的实例层,用于实际应用.

结论:

构建的谣言域本体学显示出高的一致性和可靠性.
该方法促进语义解析和推理,以改善在线谣言检测和治理.
这项工作为人工智能和信息科学领域的贡献,用于打击错误信息.

关键词:

域本体学是一个域本体学.发现新概念的发现.谣言内容的特征是谣言内容的特征.特别指令规则 (SWRL) 的规则在TFI中,我们可以看到TFI.最顶级的存在论重复使用.

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