arXiv Open Access 2020

Human-Machine Collaboration for Democratizing Data Science

Clément Gautrais Yann Dauxais Stefano Teso Samuel Kolb Gust Verbruggen +1 lainnya

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Abstrak

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.

Topik & Kata Kunci

cs.AI cs.HC

Penulis (6)

Clément Gautrais

Yann Dauxais

Stefano Teso

Samuel Kolb

Gust Verbruggen

Luc De Raedt

Format Sitasi

APA MLA BibTeX

Gautrais, C., Dauxais, Y., Teso, S., Kolb, S., Verbruggen, G., Raedt, L.D. (2020). Human-Machine Collaboration for Democratizing Data Science. https://arxiv.org/abs/2004.11113

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Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓