Task recommendation method based on the influencing factors of crowdsourcing contest participating willingness

ZHONG Qiuyan, LI Chen, CUI Shaoze

Systems Engineering - Theory & Practice ›› 2018, Vol. 38 ›› Issue (11) : 2954-2965.

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PDF(1132 KB)
Systems Engineering - Theory & Practice ›› 2018, Vol. 38 ›› Issue (11) : 2954-2965. DOI: 10.12011/1000-6788(2018)11-2954-12

Task recommendation method based on the influencing factors of crowdsourcing contest participating willingness

  • ZHONG Qiuyan, LI Chen, CUI Shaoze
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Abstract

In crowdsourcing contest, effective task recommendation becomes an urgent problem to be solved. The traditional task recommendation only builds the task recommendation method based on the worker's bidding record of the task, but the worker's bidding on the task is essentially determined by the willingness of the worker to participate. Considered the characteristics of crowdsourcing contest, a task recommendation method based on influencing factors of crowdsourcing contest participating willingness is proposed. Based on previous researches on the influencing factors of participating willingness, the influencing factors of workers' participating willingness are described as workers' preference on profits, ability and their trust in requesters. According to the behavior history of workers and related information, each dimension of the influencing factors is measured. Then, we formulate the worker model and generate recommendation list using collaborative filtering algorithm with the similarity degree of influencing factors. The numeral experiments on real data from epwk.com indicate that this method has better performance on the task recommendation of crowdsourcing contest.

Key words

crowdsourcing contest / task recommendation / participation willingness / worker model / collaborative filtering

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ZHONG Qiuyan , LI Chen , CUI Shaoze. Task recommendation method based on the influencing factors of crowdsourcing contest participating willingness. Systems Engineering - Theory & Practice, 2018, 38(11): 2954-2965 https://doi.org/10.12011/1000-6788(2018)11-2954-12

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Funding

Key Program of National Natural Science Foundation of China (71533001)
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