相关实验视频
企业业务活动的多源异质区块链数据质量评估模型
Haolin Zhang1, Ran Zhang1, Su Li1
1School of Information, Liaoning University, Shenyang, Liaoning, China.
PloS one
|June 14, 2024
概括
这项研究引入了一种新的区块链数据质量模型,用于企业. 它提高了业务活动的一致性,可信度和价值评估,优于现有方法.
科学领域:
- 计算机科学 计算机科学
- 信息系统信息系统信息系统
- 数据科学数据科学数据科学
背景情况:
- 企业区块链的采用正在增长,但现有的评估方法不足.
- 挑战包括异构的数据源,不一致的表示和信息模两可.
- 准确评估信息的一致性,可信性和价值对于商业活动至关重要.
研究的目的:
- 为企业业务活动提出一个多源异构的区块链数据质量评估模型.
- 解决目前评估区块链数据质量的方法的局限性.
- 为了使信息一致性,可信性和价值的有效评估.
主要方法:
- 开发了一种用于合并实体类别信息的代表性学习 (CEKGRL) 模型,用于实体代表性和一致性评估.
- 引入了考虑信息来源,评论和内容的可信度表征方法.
- 构建了一个区块链质量评估模型,整合了价值评估的可靠性.
主要成果:
- 拟议的模型显著改善了对区块间一致性的评估.
- 在评估区内活动信息可信度方面表现优异.
- 与现有方法相比,更好地评估区块链业务活动信息的整体价值.
结论:
- 开发的模型有效地解决了多源异质区块链数据质量的挑战.
- 它为评估企业区块链应用程序的一致性,可信度和价值提供了一个全面的框架.
- 该模型在区块链上的业务活动的当前评估技术上提供了显著的进步.
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