中文摘要：

连接数据是被大量的网代理人出版，存取，并且操作的连结资源描述框架(RDF ) 图的一个分散的空格。这里，我们在场为采矿的一个多代理人框架从连接数据，关系的发现，管理，和确认能被不同代理人独立地在执行的假想语义关系。这些代理人由出版并且交换相互依赖的知识元素在关系采矿协作，例如，假设，证据，和证明，产生连接并且评价多样的知识元素的一个证据的网络。模拟结果证明框架在多代理人环境是可伸缩的。真实世界的应用证明框架对在社会领域的学科交差、合作的关系发现任务合适。

英文摘要：

Linked data is a decentralized space of interlinked Resource Description Framework （RDF） graphs that are published, accessed, and manipulated by a multitude of Web agents. Here, we present a multi-agent framework for mining hypothetical semantic relations from linked data, in which the discovery, management, and validation of relations can be carried out independently by different agents. These agents collaborate in relation mining by publishing and exchanging inter-dependent knowledge elements, e.g., hypotheses, evidence, and proofs, giving rise to an evidentiary network that connects and ranks diverse knowledge elements. Simulation results show that the framework is scalable in a multi-agent environment. Real-world applications show that the framework is suitable for interdisciplinary and collaborative relation discovery tasks in social domains.