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Querying Graphs with Uncertain Predicates

机译:查询带有不确定谓词的图

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In many applications the available data give rise to an attributed graph, with the nodes corresponding to the entities of interest, edges to their relationships and attributes on both provide additional characteristics. To mine such data structures we have proposed a visual analytic algebra that enhances the atomic operators of selection, aggregation and a visualization step that allows the user to interact with the data. However, in many settings the user has a certain degree of uncertainty about the desired query; the problem is further compounded if the final results are the product of a series of such uncertain queries. To address this issue, we introduce a probabilistic framework that incorporates uncertainty in the queries and provides a probabilistic assessment of the likelihood of the obtained outcomes. We discuss its technical characteristics and illustrate it on a number of examples.
机译:在许多应用中,可用数据会生成一个属性图,其中对应于感兴趣实体的节点,它们之间的关系边缘和属性在这两者上都提供了额外的特征。为了挖掘此类数据结构,我们提出了一种视觉分析代数,该代数可增强选择,聚合的原子运算符,并具有可视化步骤,允许用户与数据进行交互。但是,在许多设置中,用户对所需查询有一定程度的不确定性。如果最终结果是一系列此类不确定查询的结果,则问题将进一步复杂化。为了解决这个问题,我们引入了一个概率框架,该框架在查询中纳入了不确定性,并对获得的结果的可能性进行了概率评估。我们讨论了它的技术特性,并通过许多示例对其进行了说明。

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