An endorsement-based reputation system for trustworthy crowdsourcing

An endorsement-based reputation system for trustworthy crowdsourcing
Title:
An endorsement-based reputation system for trustworthy crowdsourcing
Other Titles:
2015 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
Keywords:
Publication Date:
26 April 2015
Citation:
C. Wu, T. Luo, F. Wu and G. Chen, "An endorsement-based reputation system for trustworthy crowdsourcing," 2015 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Hong Kong, 2015, pp. 89-90. doi: 10.1109/INFCOMW.2015.7179357
Abstract:
Crowdsourcing is a new distributed computing paradigm that leverages the wisdom of crowd and the voluntary human effort to solve problems or collect data. In this paradigm of soliciting user contributions, the trustworthiness of contributions becomes a matter of crucial importance to the viability of crowdsourcing. Prior mechanisms either do not consider the trustworthiness of contributions or assess the quality of contributions only after the event, resulting in irreversible effort exertion and distorted player utilities. In this paper, we propose a reputation system to not only assess but also predict the trustworthiness of user contributions. In particular, we explore an inter-worker relationship called endorsement to improve trustworthiness prediction using machine learning methods, while taking into account the heterogeneity of both workers and tasks.
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PublisherCopyrights
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Description:
(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
ISBN:
978-1-4673-7131-5
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