Active Learning-Based Crowd Replication

Translated title of the contribution: Active Learning-Based Crowd Replication

Research output: Contribution to journalArticle

Abstract

<p>Crowd replication, which combines crowd sensing, direct observation, and mathematical modeling to enable efficient and accurate evaluation of crowd, is a low-effort, easy-to-adopt and cost-effective mechanism for crowd data collection and analysis. In crowd replication, the quality of data collection is particularly important, therefore, a novel method of data collection is proposed. We apply active learning, which is a modern method in machine learning, aiming to reduce the sample size, complexity, and increase the accuracy of the data tasks as much as possible with less data, to allow us to obtain the more informative dataset. We demonstrate with experimental results that, compared with the traditional probability-based method, our contributions enable stably capturing a more representative dataset.</p>
Translated title of the contributionActive Learning-Based Crowd Replication
Original languageJapanese
Pages (from-to)1G4ES501-1G4ES501
Journal人工知能学会全国大会論文集
Volume2020
Issue number0
DOIs
Publication statusPublished - 2020

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