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- W2894925610 abstract "Crowdsourcing has been one of focuses from scholars and businessmen along with rapid development and wide-spread applications of Internet, and platforms utilizing crowdsourcing have been popular among netizens. Among these platforms, the lack of a new worker’s capacity of accepting tasks seriously affects his/her incomes obtained by fulfilling tasks issued by requesters, which reduces his/her enthusiasm for crowdsourcing. We propose a method of accurately accepting tasks for new workers incorporating with capacities and competition intensities in this paper. In the proposed method, various types of competitions among workers are taken into consideration through information of similar tasks and workers. Then, the competitive intensity between a new worker and each of other competitors is calculated by utilizing the time consumption in fulfilling a task. Finally, the strategy of accepting tasks is generated by solving the formulated optimization problem using a genetic algorithm, with the purpose of improving the accuracy of accepting tasks. We evaluate the proposed method with data provided by Taskcn and ZBJ, the two representative commercial crowdsourcing platforms in China, and compare the results of different methods with the actual incomes. The experimental results show that the proposed method can improve the accuracy of accepting tasks, which is beneficial to increasing the labor efficiency and incomes for new workers." @default.
- W2894925610 created "2018-10-12" @default.
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- W2894925610 date "2018-01-01" @default.
- W2894925610 modified "2023-09-28" @default.
- W2894925610 title "A Method of Accurately Accepting Tasks for New Workers Incorporating with Capacities and Competition Intensities" @default.
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- W2894925610 doi "https://doi.org/10.1007/978-981-13-2829-9_18" @default.
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