Hybrid geo-information processing :crowdsourced supervision of geo-spatial machine learning tasks
This paper introduces an approach to crowdsource the supervision of machine learning classification and regression tasks in order to process geo-social media streams. It builds on a review and comparison of four existing approaches to process geo-social media streams in order to identify specific op...
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| Tác giả chính: | |
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| Định dạng: | BB |
| Ngôn ngữ: | eng |
| Thông tin xuất bản: |
2020
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| Chủ đề: | |
| Truy cập trực tuyến: | http://tailieuso.tlu.edu.vn/handle/DHTL/4718 |
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| Tóm tắt: | This paper introduces an approach to crowdsource the supervision of machine learning classification and regression tasks in order to process geo-social media streams. It builds on a review and comparison of four existing approaches to process geo-social media streams in order to identify specific opportunities and challenges. An original conceptual framework situates the machine learning tasks within a geoinformation processing workflow. The paper presents and discusses concrete techniques and software solutions for implementing it. Keywords: crowdsourcing, supervised machine learning, geo-social media streams, user-generated geographic content, volunteered geographic information. |
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