Feb 13, 2024 · We derive two lightweight and scalable algorithms: LA onepass and LA twopass. These algorithms can efficiently and effectively estimate worker qualities and ...
Nov 19, 2022 · The proposed algorithms can effectively and efficiently aggregate labels in both offline and online settings even if they traverse all the labels at most twice.
Feb 13, 2024 · We derive two lightweight and scalable algorithms: LA onepass and LA twopass. These algorithms can efficiently and effectively estimate worker qualities and ...
A Lightweight, Efective and Eficient Model for Label Aggregation in Crowdsourcing • 3. Online Aggregation. Many crowdsourcing projects are continuous and can ...
Two light-weight algorithms are derived from the dynamic model of label aggregation, which can effectively and efficiently estimate worker qualities and ...
Through experiments conducted on 20 real-world datasets, we demonstrate that our proposed algorithms can effectively and efficiently aggregate labels in both ...
LA methods estimate true labels from crowdsourced labels by modeling worker qualities. Most existing LA methods are iterative in nature. They need to traverse ...
LA methods estimate true labels from crowdsourced labels by modelling worker quality. However, most existing LA methods are iterative in nature. They require ...
This is the code of paper "A Light-weight, Effective and Efficient Model for Label Aggregation in Crowdsourcing" published on ACM Transactions on Knowledge ...
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Nov 19, 2022 · A LIGHT-WEIGHT, EFFECTIVE AND EFFICIENT MODEL FOR ... This paper presents a novel light-weight method for aggregating crowdsourced labels.