Semantic location extraction from crowdsourced data
Paper
Paper/Presentation Title | Semantic location extraction from crowdsourced data |
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Presentation Type | Paper |
Authors | Koswatte, Saman (Author), McDougall, Kevin (Author) and Liu, Xiaoye (Author) |
Journal or Proceedings Title | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
ERA Conference ID | 51072 |
Journal Citation | 41 (B2), pp. 543-547 |
Number of Pages | 4 |
Year | 2016 |
Place of Publication | Germany |
ISSN | 1682-1750 |
2194-9034 | |
Digital Object Identifier (DOI) | https://doi.org/10.5194/isprsarchives-XLI-B2-543-2016 |
Web Address (URL) of Paper | http://www.isprs2016-prague.com/ |
Conference/Event | 23rd International Society for Photogrammetry and Remote Sensing (ISPRS 2016) |
The Congress of the International Society for Photogrammetry and Remote Sensing | |
Event Details | 23rd International Society for Photogrammetry and Remote Sensing (ISPRS 2016) Event Date 12 to end of 19 Jul 2016 Event Location Prague, Czech Republic |
Event Details | The Congress of the International Society for Photogrammetry and Remote Sensing ISPRS International Society for Photogrammetry and Remote Sensing (ISPRS) |
Abstract | Crowdsourced Data (CSD) has recently received increased attention in many application areas including disaster management. Convenience of production and use, data currency and abundancy are some of the key reasons for attracting this high interest. Conversely, quality issues like incompleteness, credibility and relevancy prevent the direct use of such data in important applications like disaster management. Moreover, location information availability of CSD is problematic as it remains very low in many crowd sourced platforms such as Twitter. Also, this recorded location is mostly related to the mobile device or user location and often does not represent the event location. In CSD, event location is discussed descriptively in the comments in addition to the recorded location (which is generated by means of mobile device's GPS or mobile communication network). This study attempts to semantically extract the CSD location information with the help of an ontological Gazetteer and other available resources. 2011 Queensland flood tweets and Ushahidi Crowd Map data were semantically analysed to extract the location information with the support of Queensland Gazetteer which is converted to an ontological gazetteer and a global gazetteer. Some preliminary results show that the use of ontologies and semantics can improve the accuracy of place name identification of CSD and the process of location information extraction. |
Keywords | Geospatial Semantics, SDI, Crowdsourced Data, Ontologies, QLD Floods |
ANZSRC Field of Research 2020 | 460999. Information systems not elsewhere classified |
379999. Other earth sciences not elsewhere classified | |
Byline Affiliations | School of Civil Engineering and Surveying |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q397z/semantic-location-extraction-from-crowdsourced-data
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