Practice of Efficient Data Collection via Crowdsourcing: Aggregation, Incremental Relabelling, and Pricing

Alexey Drutsa, Valentina Fedorova, Dmitry Ustalov, Olga Megorskaya, Evfrosiniya Zerminova, Daria Baidakova
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引用次数: 8

Abstract

In this tutorial, we present a portion of unique industry experience in efficient data labelling via crowdsourcing shared by both leading researchers and engineers from Yandex. We will make an introduction to data labelling via public crowdsourcing marketplaces and will present key components of efficient label collection. This will be followed by a practice session, where participants will choose one of the real label collection tasks, experiment with selecting settings for the labelling process, and launch their label collection project on Yandex.Toloka, one of the largest crowdsourcing marketplaces. The projects will be run on real crowds within the tutorial session. Finally, participants will receive a feedback about their projects and practical advice to make them more efficient. We expect that our tutorial will address an audience with a wide range of background and interests. We do not require specific prerequisite knowledge or skills. We invite beginners, advanced specialists, and researchers to learn how to efficiently collect labelled data.
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通过众包有效收集数据的实践:聚合、增量重新标签和定价
在本教程中,我们将介绍Yandex领先的研究人员和工程师通过众包分享的有效数据标签的部分独特行业经验。我们将通过公共众包市场介绍数据标签,并将介绍有效标签收集的关键组成部分。接下来是一个练习环节,参与者将选择一个真正的标签收集任务,尝试选择标签过程的设置,并在Yandex上启动他们的标签收集项目。Toloka,最大的众包市场之一。这些项目将在辅导课程中在真实人群中进行。最后,参加者将收到有关他们的项目的反馈和实用的建议,以提高他们的效率。我们希望我们的教程能够满足具有广泛背景和兴趣的读者。我们不需要特定的先决知识或技能。我们邀请初学者,高级专家和研究人员学习如何有效地收集标记数据。
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