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arxiv 2004.11113 v1 pith:PCHIS2QS submitted 2020-04-23 cs.AI cs.HC

Human-Machine Collaboration for Democratizing Data Science

classification cs.AI cs.HC
keywords datasciencecollaborationhuman-machinespreadsheettaskstextscvisualsynth
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Everybody wants to analyse their data, but only few posses the data science expertise to to this. Motivated by this observation we introduce a novel framework and system \textsc{VisualSynth} for human-machine collaboration in data science. It wants to democratize data science by allowing users to interact with standard spreadsheet software in order to perform and automate various data analysis tasks ranging from data wrangling, data selection, clustering, constraint learning, predictive modeling and auto-completion. \textsc{VisualSynth} relies on the user providing colored sketches, i.e., coloring parts of the spreadsheet, to partially specify data science tasks, which are then determined and executed using artificial intelligence techniques.

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