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
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