基于可信度的知识图嵌入,用于识别社会品牌倡导者
Bilal Abu-Salih1, Salihah Alotaibi2, Manaf Al-Okaily3,4
1King Abdullah II School of Information Technology, The University of Jordan, Amman, Jordan.
Frontiers in big data
|December 5, 2024
概括
本研究引入了使用知识图 (KG) 识别在线有影响力的品牌倡导者的新框架. 它通过分析社交信誉和减轻垃圾邮件来增强客户参与策略.
科学领域:
- 计算机科学 计算机科学
- 社会科学 社会科学 社会科学
背景情况:
- 品牌倡导者推动积极的口碑传播 (WOM),但使用当前的系统很难识别.
- 知识图 (KG) 提供结构化数据,以了解客户的互动和偏好.
研究的目的:
- 开发一个智能系统,准确识别在线品牌倡导者.
- 增强对客户倡导动态和社会信誉的理解.
主要方法:
- 构建知识图 (KG) 来表示品牌与客户的互动.
- 使用KG嵌入技术进行链接预测,聚类和可视化.
- 整合和扩展DSpamOnto的社会垃圾邮件检测本体学.
主要成果:
- 拟议的框架准确地确定了品牌倡导者.
- 该系统有效地分析了社会信誉,以区分真正的倡导者和垃圾邮件发送者.
- 通过KG嵌入,可以有效分析和可视化倡导网络.
结论:
- 这种基于KG的新框架改善了对品牌倡导者的识别和理解.
- 整合社会可信度分析对于保持信任和真实性至关重要.
- 这种方法使企业能够优化客户参与和宣传策略.
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