Human-Machine Collaboration for Democratizing Data Science

Autor:	Gautrais, Clément, Dauxais, Yann, Teso, Stefano, Kolb, Samuel, Verbruggen, Gust, De Raedt, Luc
Rok vydání:	2020
Předmět:	Computer Science - Artificial Intelligence Computer Science - Human-Computer Interaction I.2.1 H.5.2
Druh dokumentu:	Working Paper
Popis:	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. Comment: 26 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2004.11113 Zobrazit plný text záznamu View this record from Arxiv