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Identifying and Rewarding Subcrowds in Crowdsourcing

Siyuan Liu, Xiuyi Fan, Chunyan Miao

22nd European Conference on Artificial Intelligence, Volume: 285: ECAI 2016, Pages: 1573 - 1574

Swansea University Author: Xiuyi Fan

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Abstract

Identifying and rewarding truthful workers are key to the sustainability of crowdsourcing platforms. In this paper, we present a clustering based rewarding mechanism that rewards workers based on their truthfulness while accommodating the differences in workers' preferences. Experimental result...

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Published in: 22nd European Conference on Artificial Intelligence
ISBN: 978-1-61499-671-2 978-1-61499-672-9
ISSN: 0922-6389 1879-8314
Published: The Hague, The Netherlands 22nd European Conference on Artificial Intelligence 2016
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa39397
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Abstract: Identifying and rewarding truthful workers are key to the sustainability of crowdsourcing platforms. In this paper, we present a clustering based rewarding mechanism that rewards workers based on their truthfulness while accommodating the differences in workers' preferences. Experimental results show that the proposed approach can effectively discover subcrowds under various conditions, and truthful workers are better rewarded than less truthful ones.
College: College of Science
Start Page: 1573
End Page: 1574