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Sep 17, 2012 · In this paper, we propose algorithms for integrating machine learning into crowd-sourced databases, with the goal of allowing crowd-sourcing ...
In this paper, we propose algorithms for integrating machine learning into crowd-sourced databases, with the goal of allowing crowd-sourcing applications to ...
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The paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach.
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Designing active learning algorithms for a crowd-sourced database poses many practical challenges: such algorithms need to be generic, scalable, and easy to ...
Two new active learning algorithms are presented to combine humans and algorithms together in a crowd-sourced database, based on the theory of ...
In this work, we show how to collect and use human feedback to improve complex models in information retrieval systems. Human feedback often improves model ...
May 30, 2021 · We provide a comprehensive and systematic survey of the recent research on active learning in the hybrid human–machine classification setting, ...
Designing active learning algorithms for a crowd-sourced database poses many practical challenges: such algorithms need to be generic, scalable, and easy to use ...
This paper proposes algorithms for in- tegrating machine learning into crowd-sourced databases in order to combine the accuracy of human labeling with the speed ...
Bibliographic details on Active Learning for Crowd-Sourced Databases.