CrowdRev: A platform for Crowd-based Screening of Literature Reviews
May 31, 2018 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Jorge Ramirez, Evgeny Krivosheev, Marcos Baez, Fabio Casati, Boualem Benatallah
arXiv ID
1805.12376
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.DL
Citations
10
Venue
arXiv.org
Last Checked
4 months ago
Abstract
In this paper and demo we present a crowd and crowd+AI based system, called CrowdRev, supporting the screening phase of literature reviews and achieving the same quality as author classification at a fraction of the cost, and near-instantly. CrowdRev makes it easy for authors to leverage the crowd, and ensures that no money is wasted even in the face of difficult papers or criteria: if the system detects that the task is too hard for the crowd, it just gives up trying (for that paper, or for that criteria, or altogether), without wasting money and never compromising on quality.
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