Name
Abstract | ||
|---|---|---|
The advent of volunteered geographical information VGI has contributed to the growth of the amount of user-contributed spatial data around the world. Spatial data acquired from crowdsourcing environments may contain valuable information which can be useful in other research fields, such as Digital gazetteers, commonly used in Geographic Information Retrieval. Digital gazetteers have a powerful role in the geoparsing process. They need to be kept up-to-date and as comprehensive as possible to enable geoparsers to perform lookup and then resolve toponym recognition precisely over digital documents. The detection of toponyms in digital texts such as social media posts is a bottom line for discovering useful spatially related information such as complaints regarding urban areas. In this context, this article proposes a method for gazetteer enrichment leveraging VGI data sources. Indeed VGI environments are not originally developed to work as gazetteers, however, they often contain more detailed and up-to-date information than gazetteers. Our method is applied within a geoparser environment by adapting its heuristics set besides enriching the corresponding gazetteer. A case study was performed by geoparsing Twitter posts focusing solely on the messages aiming at evaluating the performance of the enriched system. The obtained results were encouraging and have provided a good basis for discussion. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1080/17489725.2016.1196755 | J. Location Based Services |
Keywords | Field | DocType |
Gazetteer, geoparsing, OpenStreetMap, Twitter, VGI | Spatial analysis,Data mining,Social media,Computer science,Crowdsourcing,Geoparsing,Geographic information retrieval,Heuristics,Volunteered geographic information,Multimedia | Journal |
Volume | Issue | ISSN |
10 | 2 | 1748-9725 |
Citations | PageRank | References |
3 | 0.39 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maxwell Guimarães de Oliveira | 1 | 24 | 7.15 |
| Cláudio Elízio Calazans Campelo | 2 | 22 | 5.47 |
| Cláudio de Souza Baptista | 3 | 133 | 31.73 |
| Michela Bertolotto | 4 | 863 | 91.77 |