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Creators/Authors contains: "Weikum, Gerhard"

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  1. ; ; ; ; (, HILDA'23: The SIGMOD 2023 Workshop on Human-in-the-Loop Data Analytics)
    Open knowledge, including open data and publicly available knowledge bases, offers a rich opportunity for data scientists for analysis and query answering, but comes with big obstacles due to the diverse, noisy, and incomplete nature of its data eco-system. This paper proposes a vision for enabling approximate QUery answering over Open Knowledge (Quok), with a focus on supporting analytic tasks that involve identifying relevant data and computing aggregations. We define the problem, outline a system architecture, and discuss challenges and approaches to taming the uncertainty and incompleteness of open knowledge. 
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