2018/05/31 by Jorge Ramírez, Evgeny Krivosheev, Ramirez, Jorge +7
Computer Science · #Data Stream Mining Techniques #Digital Libraries (cs.DL) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Mobile Crowdsensing and Crowdsourcing #Software Engineering Research
paper · pdf · doi:10.48550/arxiv.1805.12376
openalex publication_date 2018/05/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.