Item Infomation
Title: | Hybrid geo-information processing :crowdsourced supervision of geo-spatial machine learning tasks |
Authors: | Ostermann, Frank O. |
Issue Date: | 2014 |
Citation: | In: Proceedings of the 18th AGILE International conference on geographic information science, 9-12 June 2015, Lisbon, Portugal. AGILE, 2015. 4 p |
Abstract: | 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. |
URI: | http://tailieuso.tlu.edu.vn/handle/DHTL/4718 |
Source: | https://agile-online.org/Conference_Paper/cds/agile_2015/shortpapers/78/78_Paper_in_PDF.pdf |
Appears in Collections: | Tài liệu mở |
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