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クラウドソーシングワーカーの段階的育成方法の提案
https://uec.repo.nii.ac.jp/records/9061
https://uec.repo.nii.ac.jp/records/90618b749109-eba5-4c7b-b4be-5e77d7f8c922
| 名前 / ファイル | ライセンス | アクション |
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32_B-G81 (4.9 MB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||||||||||||||||||||
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| 公開日 | 2019-04-04 | |||||||||||||||||||||||
| タイトル | ||||||||||||||||||||||||
| タイトル | クラウドソーシングワーカーの段階的育成方法の提案 | |||||||||||||||||||||||
| 言語 | ja | |||||||||||||||||||||||
| タイトル | ||||||||||||||||||||||||
| タイトル | Crowdsourcing Worker Development based on Probabilistic Task Network | |||||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||||
| 言語 | ||||||||||||||||||||||||
| 言語 | jpn | |||||||||||||||||||||||
| キーワード | ||||||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||||
| 主題 | crowdsourcing | |||||||||||||||||||||||
| キーワード | ||||||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||||
| 主題 | education | |||||||||||||||||||||||
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| 言語 | en | |||||||||||||||||||||||
| 主題 | bayesian network | |||||||||||||||||||||||
| 資源タイプ | ||||||||||||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||||||||||||
| 資源タイプ | journal article | |||||||||||||||||||||||
| 著者 |
芦川, 将之
× 芦川, 将之
× 川村, 隆浩
× 大須賀, 昭彦
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| 抄録 | ||||||||||||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||||||||||||
| 内容記述 | Current crowdsourcing platforms such as Amazon Mechanical Turk provide an attractive solution Crowdsourcing platforms provide an attractive solution for processing numerous tasks at a low cost. However, insufficient quality control remains a major concern. Therefore, we developed a private crowdsourcing system that allows us to devise quality control methods. In the present study, we propose a grade-based training method for workers in order to avoid simple exclusion of low-quality workers and shrinkage of the crowdsourcing market in the near future. Our training method utilizes probabilistic networks to estimate correlations between tasks based on workers’ records for 18.5 million tasks and then allocates pre-learning tasks to the workers to raise the accuracy of target tasks according to the task correlations. In an experiment, the method automatically allocated 31 pre-learning task categories for 9 target task categories, and after the training of the pre-learning tasks, we confirmed that the accuracy of the target tasks was raised by 7.8 points on average. This result was comparatively higher than those of pre-learning tasks allocated using other methods, such as decision trees. We thus confirmed that the task correlations can be estimated using a large amount of worker records, and that these are useful for the grade-based training of low-quality workers. | |||||||||||||||||||||||
| 書誌情報 |
ja : 人工知能学会論文誌 en : Transactions of the Japanese Society for Artificial Intelligence 巻 32, 号 3, p. B-G81_1-13, 発行日 2017-05-01 |
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| 出版者 | ||||||||||||||||||||||||
| 出版者 | 人工知能学会 | |||||||||||||||||||||||
| ISSN | ||||||||||||||||||||||||
| 収録物識別子タイプ | ISSN | |||||||||||||||||||||||
| 収録物識別子 | 1346-0714 | |||||||||||||||||||||||
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| 関連タイプ | isIdenticalTo | |||||||||||||||||||||||
| 識別子タイプ | DOI | |||||||||||||||||||||||
| 関連識別子 | 10.1527/tjsai.B-G81 | |||||||||||||||||||||||
| 権利 | ||||||||||||||||||||||||
| 権利情報 | Copyright © 人工知能学会 2018 | |||||||||||||||||||||||
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| 識別子タイプ | DOI | |||||||||||||||||||||||
| 関連識別子 | https://doi.org/10.1527/tjsai.B-G81 | |||||||||||||||||||||||
| 著者版フラグ | ||||||||||||||||||||||||
| 出版タイプ | VoR | |||||||||||||||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||||||||||||||
