Statistical Decision Making for Budget Allocation in Crowdsourcing
نویسنده
چکیده
In this short paper, we briefly describe some recent progress on statistical decision making for budget allocation in crowdsourcing. We address the budget allocation problem for two important labeling tasks in crowdsourcing: the categorization labeling task and pairwise ranking aggregation. We also show the connections between our work and the “proactive learning” framework proposed by Jaime Carbonell.
منابع مشابه
Statistical decision making for optimal budget allocation in crowd labeling
It has become increasingly popular to obtain machine learning labels through commercial crowdsourcing services. The crowdsourcing workers or annotators are paid for each label they provide, but the task requester usually has only a limited amount of the budget. Since the data instances have different levels of labeling difficulty and the workers have different reliability for the labeling task,...
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