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The missing path: Analysing incompleteness in knowledge graphs

机译:缺失的路径:在知识图中分析不完整性

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Knowledge Graphs (KG) allow to merge and connect heterogeneous data despite their differences; they are incomplete by design. Yet, KG data producers need to ensure the best level of completeness, as far as possible. The difficulty is that they have no means to distinguish cases where incomplete entities could and should be fixed. We present a new visualization tool: The Missing Path, to support them in identifying coherent subsets of entities that can be repaired. It relies on a map, grouping entities according to their incomplete profile. The map is coordinated with histograms and stacked charts to support interactive exploration and analysis; the summary of a subset can be compared with the one of the full collection to reveal its distinctive features. We conduct an iterative design process and evaluation with nine Wikidata contributors. Participants gain insights and find various strategies to identify coherent subsets to be fixed.
机译:尽管有所不同,但知识图(kg)允许合并和连接异构数据;它们是不完整的设计。然而,kg数据生产者需要确保尽可能确保最佳的完整性水平。难点是他们没有意味着区分不完全实体可以并且应该固定的情况。我们提出了一个新的可视化工具:缺失路径,支持它们识别可以修复的实体的连贯子集。它依赖于地图,根据其不完整的配置文件进行分组实体。地图与直方图和堆叠图表协调,以支持交互式探索和分析;可以将子集的摘要与其中一个完整集合进行比较,以揭示其独特的特征。我们用九个Wikidata贡献者进行迭代设计过程和评估。参与者获得见解并找到各种策略来确定要修复的连贯子集。

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