ACM Transactions on Intelligent Systems and Technology (TIST) - Special Issue on Crowd in Intelligent Systems, Research Note/Short Paper and Regular Papers: Volume 7 Issue 4, July 2016
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We present an incremental Bayesian model that resolves key issues of crowd size and data quality for consensus labeling. We evaluate our method using data collected from a real-world citizen science program, B ee W atch , which invites members of the public in the United Kingdom to classify (label) ...
Crowdsourcing, consensus model, bumblebee identification, Bayesian reasoning, biological recording, citizen science