EndorTrust: An endorsement-based reputation system for trustworthy and heterogeneous crowdsourcing

Chunchun Wu; Tie Luo; Fan Wu; Guihai Chen

doi:10.1109/GLOCOM.2014.7417352

EndorTrust: An endorsement-based reputation system for trustworthy and heterogeneous crowdsourcing

Chunchun Wu, Tie Luo, Fan Wu, Guihai Chen

Electrical and Computer Engineering

Research output: Contribution to journal › Conference article › peer-review

19 Scopus citations

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 context, trustworthiness of user contributions is of crucial importance to the viability of crowdsourcing. Prior mechanisms either do not consider the trustworthiness or quality of contributions or have to assess it only after workers' submission of contributions, which results in irreversible effort expenditure and negative player utilities. In this paper, we propose a reputation system, EndorTrust, to not only assess but also predict the trustworthiness of contributions without wasting workers' effort. The key approach is to explore an inter-worker relationship called endorsement to improve trustworthiness prediction using machine learning methods, while also taking into account the heterogeneity of both workers and tasks.

Original language	English
Article number	7417352
Journal	Proceedings - IEEE Global Communications Conference, GLOBECOM
DOIs	https://doi.org/10.1109/GLOCOM.2014.7417352
State	Published - 2015
Event	58th IEEE Global Communications Conference, GLOBECOM 2015 - San Diego, United States Duration: Dec 6 2015 → Dec 10 2015

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Funding

This work was supported in part by the State Key Development Program for Basic Research of China (973 project 2014CB340303), in part by China NSF grant 61422208, 61472252, 61272443 and 61133006, in part by CCFIntel Young Faculty Researcher Program and CCF-Tencent Open Fund, in part by the Scientific Research Foundation for the Returned Overseas Chinese Scholars, in part by Jiangsu Future Network Research Project No. BY2013095-1-10, and in part by ASTAR Singapore under SERC grant 1224104046. The opinions, findings, conclusions, and recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the funding agencies or the government

Funders	Funder number
ASTAR Singapore
CCF-Tencent Open Fund
CCFIntel
NSF of China	61272443, 61472252, 61133006, 61422208
Jiangsu Future Network Research	BY2013095-1-10
UK Science and Engineering Research Council	1224104046
Major State Basic Research Development Program of China	2014CB340303
Scientific Research Foundation for Returned Scholars of Ministry of Education

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Hardware and Architecture
Signal Processing

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10.1109/GLOCOM.2014.7417352

Cite this

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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 context, trustworthiness of user contributions is of crucial importance to the viability of crowdsourcing. Prior mechanisms either do not consider the trustworthiness or quality of contributions or have to assess it only after workers' submission of contributions, which results in irreversible effort expenditure and negative player utilities. In this paper, we propose a reputation system, EndorTrust, to not only assess but also predict the trustworthiness of contributions without wasting workers' effort. The key approach is to explore an inter-worker relationship called endorsement to improve trustworthiness prediction using machine learning methods, while also taking into account the heterogeneity of both workers and tasks.",

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EndorTrust: An endorsement-based reputation system for trustworthy and heterogeneous crowdsourcing

Abstract

Bibliographical note

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ASJC Scopus subject areas

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