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Preface: The 2019 ACM SIGKDD Workshop on Causal Discovery

机译:前言:2019年ACM SIGKDD因果发现研讨会

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Discovering causal relationships is the ultimate goal of many scientific explorations.However, it is not feasible to conduct randomized controlled trials in most cases. Discoveringcausal relationships in large databases of observational data is therefore very important,but it is also a challenging problem. There has been an increasing interest in discoveringcausal relationships based on observational data, and in the past few decades, significantcontributions have been made to this field by computer scientists.
机译:发现因果关系是许多科学探索的最终目标。但是,在大多数情况下进行随机对照试验是不可行的。因此,在大型观测数据数据库中发现因果关系非常重要,但这也是一个具有挑战性的问题。人们越来越关注基于观测数据发现因果关系,并且在过去的几十年中,计算机科学家在这一领域做出了重大贡献。

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