Efficient Task Decomposition for Sequential Crowdsourced Task Solving  

作　　者：JIANG Huan ZUO Min MATSUBARA Shigeo 

机构地区：[1]National Engineering Laboratory for Agri-product Quality Traceability,School of Computer and Information Engineering,Beijing Technology and Business University,Beijing 100048,China [2]Department of Social Informatics,Kyoto University,Kyoto 606-8501,Japan

出　　处：《Chinese Journal of Electronics》2020年第3期468-475,共8页电子学报（英文版）

基　　金：This work is supported by the National Key Research and Development Project(No.2016YFD0401205);Humanity and Social Science Youth Foundation of Ministry of Education of China(No.17YJCZH007);Beijing Natural Science Foundation(No.4202014);JSPS KAKENHI(No.JP17H00759 and No.JP19H04170).

摘　　要：In order to facilitate crowdsourcing-based task solving,complex tasks are decomposed into smaller subtasks that can be executed by individual workers.Decomposing task into sequential subtasks attracts a plenty of empirical explorations.The absence of formal studies makes it difficult to provide task requesters with explicit guidelines on task decomposition strategy.We formally present the vertical task decomposition model by specifying the positive quality dependencies among sequential subtasks.Our focus is on addressing solutions of low quality intentionally provided by selfinterested workers who are paid equally or based on their contributions.By combining the theoretical analysis on workers'strategic behaviors and experimental exploration on the efficiency of task decomposition,our study demonstrates the relationship between the incentive and the worker's performance,and gives the explicit instructions on vertical task decomposition,which show promise on improving the quality of the final outcome.

关 键 词：Crowdsourcing Task decomposition Subtask dependence Solution quality Revenue sharing 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]