A Survey of Crowdsourcing Methods for Commonsense Knowledge Collection

Bachelor thesis (2022)

Authors

I.E.I. Renţea Electrical Engineering, Mathematics and Computer Science

Contributors

G. He Web Information Systems - EEMCS (supervisor 1)
Ujwal Gadiraju Web Information Systems - EEMCS (supervisor 1)
J. Yang Web Information Systems - EEMCS (supervisor 1)
G.J.P.M. Houben Web Information Systems - EEMCS (supervisor 2)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Ilinca Renţea
Efficiency Commonsense Knowledge Survey Crowdsourcing Cost Quality GWAP Knowledge Acquisition System
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Published Date

24-06-2022

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Commonsense knowledge is information that all humans own and use to interpret common situations and react to them accordingly. This kind of information is necessary for the training of artificial intelligence models to reach a performance as close as possible to human performance. Researchers have developed methods that use crowdsourcing to collect this kind of knowledge from the general public. This research focuses on systematically surveying the existing literature about these methods. We created a taxonomy to describe and compare the existing work based on the following three measures that were the most common ones reported: efficiency, cost, and quality.