Human-Machine Collaboration for Democratizing Data Science
April 23, 2020 Β· Declared Dead Β· π Human-Like Machine Intelligence
"No code URL or promise found in abstract"
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Authors
ClΓ©ment Gautrais, Yann Dauxais, Stefano Teso, Samuel Kolb, Gust Verbruggen, Luc De Raedt
arXiv ID
2004.11113
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.HC
Citations
3
Venue
Human-Like Machine Intelligence
Last Checked
4 months ago
Abstract
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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