Active Learning-Based Crowd Replication

研究成果: Contribution to journalArticle

抄録

<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>
寄稿の翻訳タイトルActive Learning-Based Crowd Replication
本文言語Japanese
ページ(範囲)1G4ES501-1G4ES501
ジャーナル人工知能学会全国大会論文集
2020
0
DOI
出版ステータス出版済み - 2020

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