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Data Conflict Resolution Using Trust Mappings

机译:使用信任映射数据冲突解决

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In massively collaborative projects such as scientific or community databases, users often need to agree or disagree on the content of individual data items. On the other hand, trust relationships often exist between users, allowing them to accept or reject other users' beliefs by default. As those trust relationships become complex, however, it becomes difficult to define and compute a consistent snapshot of the conflicting information. Previous solutions to a related problem, the update reconciliation problem, are dependent on the order in which the updates are processed and, therefore, do not guarantee a globally consistent snapshot. This paper proposes the first principled solution to the automatic conflict resolution problem, in a community database. Our semantics is based on the certain tuples of all stable models of a logic program. While evaluating stable models in general is well known to be hard, even for very simple logic programs, we show that the conflict resolution problem admits a PTIME solution. To the best of our knowledge, ours is the first PTIME algorithm that allows conflict resolution in a principled way. We further discuss extensions to negative beliefs and prove that some of these extensions are hard. This work is done in the context of the Beliej'DB project at the University of Washington, which focuses on the efficient management of conflicts in community databases.
机译:在科学或社区数据库等大规模协作项目中,用户通常需要同意或不同意各个数据项的内容。另一方面,用户之间通常存在信任关系,默认情况下,允许它们接受或拒绝其他用户的信念。然而,由于这些信任关系变得复杂,因此难以定义和计算冲突信息的一致快照。先前的相关问题,更新协调问题,依赖于处理更新的顺序,因此,不保证全局一致的快照。本文提出了第一个原则性解决自动冲突解决问题的原因解决方案,在社区数据库中。我们的语义基于逻辑程序的所有稳定模型的某些元组。虽然评估稳定模型一般众所周知,即使对于非常简单的逻辑计划,也表明冲突解决问题承认了一个PTIME解决方案。据我们所知,我们的是第一个以原则方式解决冲突解决方案算法。我们进一步讨论了对负面信的延伸,并证明了一些这些扩展很难。这项工作是在华盛顿大学的Beliej'db项目的背景下完成的,专注于社区数据库中的冲突的有效管理。

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