在分散的社会网络中捕获和跟踪来源的本体模型和服务

Cíntia Souza, José Ronaldo Júnior, Cássio V. S. Prazeres
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引用次数: 0

摘要

分散式在线社交网络(dosn)的兴起以及这些网络上活跃用户数量的增加为开发与验证来源、描述路径和指示这些网络中流量数据轨迹相关的解决方案提供了机会。来源信息是社交网络的一个关键方面,因为它可以通过其结果评估信息的真实性、可靠性和相关性。信息生成和共享的速度以及与大量数据相关的分散存储策略对数据来源提出了挑战。为此,本文提出了基于W3C provo规范的数据来源本体模型dosnprove。此外,本文还提出了基于dosn - proof模型的服务,以支持dosn中来源信息的捕获和跟踪。我们分两个阶段对DOSN-PROV模型进行了评估,并证明了其质量和符合所提出的领域。对这些服务的性能进行了评估,评估结果表明了可接受的响应时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Ontological Model and Services for Capturing and Tracking Provenance in Decentralized Social Networks
The rise of Decentralized Online Social Networks (DOSNs) and the increase in the number of active users on these networks offer an opportunity to develop solutions related to verifying origin, description paths and indicating the trajectory of the data that traffic in these networks. Provenance information is a key aspect of social networks because it is possible to evaluate the authenticity, reliability, and relevance of the information through its results. The speed of information generation and sharing, the decentralized storage strategy associated with the large volume of data represents a challenge for data provenance. Thus, this paper proposes DOSNPROV, a data provenance ontological model based on the W3C PROV-O specification. In addition, this paper proposes services based on DOSN-PROV model to support capture and tracking of provenance information in DOSNs. We evaluated DOSN-PROV model in two stages and demonstrated its quality and compliance with the proposed domain. The services underwent an evaluation of their performance and their results indicated acceptable response times.
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