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Causality and explanations in databases
2014
Proceedings of the VLDB Endowment
With the surge in the availability of information, there is a great demand for tools that assist users in understanding their data. While today's exploration tools rely mostly on data visualization, users often want to go deeper and understand the underlying causes of a particular observation. This tutorial surveys research on causality and explanation for data-oriented applications. We will review and summarize the research thus far into causality and explanation in the database and AI
doi:10.14778/2733004.2733070
fatcat:2a6yqccrjrfitdv4tqshxtfkpm