Auction Based Mechanisms for Dynamic Task Assignments in Expert Crowdsourcing
Auction Based Mechanisms for Dynamic Task Assignments in Expert Crowdsourcing
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DOI：
10.1007/978-3-319-54229-4_4
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发表时间：
2015-05
期刊：
影响因子：
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通讯作者：
Sujit Gujar;B. Faltings
中科院分区：
文献类型：
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作者：
Sujit Gujar;B. Faltings
众包市场将大量员工与更多的任务联系在一起。因此，有必要建立机制，将员工与有趣和合适的任务相匹配。早期的工作已经解决了为给定的一组任务寻找最佳工作人员的问题。然而，员工也有偏好，只有当平台给他们提供有趣的任务时，他们才会留在平台上。因此，我们还分析了几种考虑工人偏好的匹配机制。我们建议工人支付保费以获得首选匹配和基于拍卖的模型，其中偏好通过任务付款的变化来表达。我们分析了两种匹配的不同机制：分裂动态向量组(SDV)和电子拍卖。我们将这两种机制与到达优先序列独裁机制(APSD)进行了效率的实证比较。
Crowdsourcing marketplaces link large populations of workers to an even larger number of tasks. Thus, it is necessary to have mechanisms for matching workers with interesting and suitable tasks. Earlier work has addressed the problem of finding optimal workers for a given set of tasks. However, workers also have preferences and will stay with a platform only if it gives them interesting tasks. We therefore analyze several matching mechanisms that take into account workers’ preferences as well. We propose that the workers pay premiums to get preferred matches and auction-based models where preferences are expressed through variations of the payment for a task. We analyze the properties of two matching different mechanisms: Split Dynamic VCG (SDV) and e-Auction. We compare both the mechanisms with Arrival Priority Serial Dictatorship (APSD) empirically for efficiency.