Active Learning Based on Crowdsourced Data
The paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or...
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Format: | Article |
Language: | English |
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MDPI AG
2022-01-01
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Series: | Applied Sciences |
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Online Access: | https://www.mdpi.com/2076-3417/12/1/409 |
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author | Tomasz Maria Boiński Julian Szymański Agata Krauzewicz |
author_facet | Tomasz Maria Boiński Julian Szymański Agata Krauzewicz |
author_sort | Tomasz Maria Boiński |
collection | DOAJ |
description | The paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or not. The proposed solution reduces the amount of work needed to annotate large sets of data. Furthermore, it allows a perpetual increase in the trained network quality by the inclusion of new samples, gathered after network deployment. The paper also discusses means of limiting network training times, especially in the post-deployment stage, where the size of the training set can increase dramatically. This is done by the introduction of the fourth set composed of samples gather during network actual usage. |
first_indexed | 2024-03-10T03:49:29Z |
format | Article |
id | doaj.art-9c692680138943f499773f4864d5d473 |
institution | Directory Open Access Journal |
issn | 2076-3417 |
language | English |
last_indexed | 2024-03-10T03:49:29Z |
publishDate | 2022-01-01 |
publisher | MDPI AG |
record_format | Article |
series | Applied Sciences |
spelling | doaj.art-9c692680138943f499773f4864d5d4732023-11-23T11:12:35ZengMDPI AGApplied Sciences2076-34172022-01-0112140910.3390/app12010409Active Learning Based on Crowdsourced DataTomasz Maria Boiński0Julian Szymański1Agata Krauzewicz2Faculty of Electronics, Telecommunication and Informatics, Gdańsk University of Technology, 80-233 Gdańsk, PolandFaculty of Electronics, Telecommunication and Informatics, Gdańsk University of Technology, 80-233 Gdańsk, PolandFaculty of Electronics, Telecommunication and Informatics, Gdańsk University of Technology, 80-233 Gdańsk, PolandThe paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to judge whether the given sample is informative or not. The proposed solution reduces the amount of work needed to annotate large sets of data. Furthermore, it allows a perpetual increase in the trained network quality by the inclusion of new samples, gathered after network deployment. The paper also discusses means of limiting network training times, especially in the post-deployment stage, where the size of the training set can increase dramatically. This is done by the introduction of the fourth set composed of samples gather during network actual usage.https://www.mdpi.com/2076-3417/12/1/409active learningsample assessmentcrowdsourcing |
spellingShingle | Tomasz Maria Boiński Julian Szymański Agata Krauzewicz Active Learning Based on Crowdsourced Data Applied Sciences active learning sample assessment crowdsourcing |
title | Active Learning Based on Crowdsourced Data |
title_full | Active Learning Based on Crowdsourced Data |
title_fullStr | Active Learning Based on Crowdsourced Data |
title_full_unstemmed | Active Learning Based on Crowdsourced Data |
title_short | Active Learning Based on Crowdsourced Data |
title_sort | active learning based on crowdsourced data |
topic | active learning sample assessment crowdsourcing |
url | https://www.mdpi.com/2076-3417/12/1/409 |
work_keys_str_mv | AT tomaszmariaboinski activelearningbasedoncrowdsourceddata AT julianszymanski activelearningbasedoncrowdsourceddata AT agatakrauzewicz activelearningbasedoncrowdsourceddata |