SNEToolkit: Spatial named entities disambiguation toolkit
“Can you tell me where San Jose is located?” “Uh! Do you know that there are more than 1700 locations named San Jose in the world?” The official name of a location is often not the name with which we are familiar. Spatial named entity (SNE) disambiguation is the process of identifying and assigning...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-07-01
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| Series: | SoftwareX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352711023001760 |
| _version_ | 1797679457841971200 |
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| author | Rodrique Kafando Rémy Decoupes Mathieu Roche Maguelonne Teisseire |
| author_facet | Rodrique Kafando Rémy Decoupes Mathieu Roche Maguelonne Teisseire |
| author_sort | Rodrique Kafando |
| collection | DOAJ |
| description | “Can you tell me where San Jose is located?” “Uh! Do you know that there are more than 1700 locations named San Jose in the world?” The official name of a location is often not the name with which we are familiar. Spatial named entity (SNE) disambiguation is the process of identifying and assigning precise coordinates to a place name that can be identified in a text. This task is not always straightforward, especially when the place name in question is ambiguous for various reasons. In this context, we are interested in the disambiguation of spatial named entities that can be identified in a textual document on a country level. The solution that we propose is based on a set of techniques that allow us to disambiguate the spatial entity considering the context in which it is mentioned from a certain number of characteristics that are specific to it. The solution uses as input a textual document and extricates the named entities identified therein while associating them with the correct coordinates. SNE disambiguation is designed to support the process of fast exploration of spatiotemporal data analysis, most often for event tracking. The proposed approach was tested on 1360 SNEs extracted from the GeoVirus dataset. The results show that SNEToolkit outperformed the baseline, the standard Geonames geocoder, with a recall value of 0.911 against a recall value of 0.871 for the baseline. A flexible Python package is provided for end users. |
| first_indexed | 2024-03-11T23:14:57Z |
| format | Article |
| id | doaj.art-d5969d2abfb748038ef8a0da8e201c37 |
| institution | Directory Open Access Journal |
| issn | 2352-7110 |
| language | English |
| last_indexed | 2024-03-11T23:14:57Z |
| publishDate | 2023-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | SoftwareX |
| spelling | doaj.art-d5969d2abfb748038ef8a0da8e201c372023-09-21T04:37:38ZengElsevierSoftwareX2352-71102023-07-0123101480SNEToolkit: Spatial named entities disambiguation toolkitRodrique Kafando0Rémy Decoupes1Mathieu Roche2Maguelonne Teisseire3TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, 500 rue Jean François Breton, Montpellier, 34090, France; CITADEL, Univ. Virtuelle BF, Ouagadougou, Burkina FasoTETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, 500 rue Jean François Breton, Montpellier, 34090, FranceTETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, 500 rue Jean François Breton, Montpellier, 34090, France; CIRAD, F-34398 Montpellier, FranceTETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, 500 rue Jean François Breton, Montpellier, 34090, France; Corresponding author.“Can you tell me where San Jose is located?” “Uh! Do you know that there are more than 1700 locations named San Jose in the world?” The official name of a location is often not the name with which we are familiar. Spatial named entity (SNE) disambiguation is the process of identifying and assigning precise coordinates to a place name that can be identified in a text. This task is not always straightforward, especially when the place name in question is ambiguous for various reasons. In this context, we are interested in the disambiguation of spatial named entities that can be identified in a textual document on a country level. The solution that we propose is based on a set of techniques that allow us to disambiguate the spatial entity considering the context in which it is mentioned from a certain number of characteristics that are specific to it. The solution uses as input a textual document and extricates the named entities identified therein while associating them with the correct coordinates. SNE disambiguation is designed to support the process of fast exploration of spatiotemporal data analysis, most often for event tracking. The proposed approach was tested on 1360 SNEs extracted from the GeoVirus dataset. The results show that SNEToolkit outperformed the baseline, the standard Geonames geocoder, with a recall value of 0.911 against a recall value of 0.871 for the baseline. A flexible Python package is provided for end users.http://www.sciencedirect.com/science/article/pii/S2352711023001760Spatial named entityDisambiguationGeocodingSoftware |
| spellingShingle | Rodrique Kafando Rémy Decoupes Mathieu Roche Maguelonne Teisseire SNEToolkit: Spatial named entities disambiguation toolkit SoftwareX Spatial named entity Disambiguation Geocoding Software |
| title | SNEToolkit: Spatial named entities disambiguation toolkit |
| title_full | SNEToolkit: Spatial named entities disambiguation toolkit |
| title_fullStr | SNEToolkit: Spatial named entities disambiguation toolkit |
| title_full_unstemmed | SNEToolkit: Spatial named entities disambiguation toolkit |
| title_short | SNEToolkit: Spatial named entities disambiguation toolkit |
| title_sort | snetoolkit spatial named entities disambiguation toolkit |
| topic | Spatial named entity Disambiguation Geocoding Software |
| url | http://www.sciencedirect.com/science/article/pii/S2352711023001760 |
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