Gazetteer enrichment for addressing urban areas: a case study

Oliveira, Maxwell Guimarães de; Campelo, Cláudio E. C.; Baptista, Cláudio de Souza; Bertolotto, Michela

doi:10.1080/17489725.2016.1196755

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…The experimental results show that the proposed method can give a richer structure and an improved coverage in comparison with another known study of automatically building a geographic database. Oliveira et al [7] proposed a novel approach for enriching the GeoSEn gazetteer [17] by using the geographical information that is gathered through crowd sourcing. The authors expanded the spatial hierarchy of the gazetteer by adding places at what appears to be district and street granularity.…”

Section: B Automatic Gazetteer Expansion or Enrichmentmentioning

confidence: 99%

Estimating Bounding Box for Point of Interest Using Social Media Geo-Tagged Photos

Bui

2023

IEEE Access

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The accuracy and completeness of information in geographical databases are very important for many location-based applications and services. However, the incompleteness in geographical databases is currently an issue. One consequence of this is that the geographic bounding boxes of many points of interests (POIs) have not been known. This paper studies the problem of estimating geographic bounding boxes for POIs using geo-tagged photos contributed by public users on social media. We present a novel approach using relevant geo-tagged photos of POIs to estimate geographic bounding boxes for the POIs. In the proposed method, we extend to apply survival analysis with random distance variable for our estimation. We demonstrate the superiority and effectiveness of our proposed approach over competing methods.INDEX TERMS Geographic bounding box, POI, survival analysis, geo-tagged photos, Flickr.

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Section: B Automatic Gazetteer Expansion or Enrichmentmentioning

confidence: 99%

Estimating Bounding Box for Point of Interest Using Social Media Geo-Tagged Photos

Bui

2023

IEEE Access

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“…Different ways of obtaining toponyms data include making field visits, personal interviews, ethnographic surveys, focus group discussions and questionnaire surveys. The use of the methods and the challenges that may arise lies in the documentation and easy access or reference; a case which has made most National Mapping Agencies (NMA) seek volunteer contributed data for enriching gazetteer data (Gao et al, 2017 ; Keßler et al, 2009 ; Oliveira et al, 2016 ). Currently, mobile applications help in collecting data on toponym heritage (Baglioni et al, 2007 ; Robinson et al, 2017 ) in addition to classical methods.…”

Section: Introductionmentioning

confidence: 99%

Citizen science characterization of meanings of toponyms of Kenya: a shared heritage

Nyangweso

Gede

2022

GeoJournal

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This paper examines the toponymic heritage used in Kenya’s Authoritative Geographic Information (AGI) toponyms database of 26,600 gazetteer records through documentation and characterization of meanings of place names in topographic mapping. A comparison was carried out between AGI and GeoNames and between AGI and OpenStreetMap (OSM) volunteered records. A total of 15,000 toponymic matchings were found. Out of these, 1567 toponyms were then extracted for further scrutiny using AGI data in the historical records and from respondents on toponyms’ meanings. Experts in toponymy assisted in verifying these data. From the questionnaire responses, 235 names occurred in more than one place while AGI data had 284. The elements used to characterize the toponyms included historical perceptions of heritage evident in toponyms in their localities, ethnographic, toponymical and morphology studies on Kenya's dialects. There was no significant relationship established between the same place name usages among dialects as indicated by a positive weak correlation r (438), = 0.166, p < 0.001 based on the effect of using the related places and the distance between related places. The weak correlation implies that the one name one place principle does not apply due to diverse language boundaries, strong bonds associated with historical toponyms in the form of heritage and significant variations on how names resist changes to preserve their heritage.

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A quantitative analysis of global gazetteers: Patterns of coverage for common feature types

Acheson

Sabbata

Purves

2017

Computers, Environment and Urban Systems

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Gazetteer enrichment for addressing urban areas: a case study

Cited by 5 publications

References 8 publications

Estimating Bounding Box for Point of Interest Using Social Media Geo-Tagged Photos

Estimating Bounding Box for Point of Interest Using Social Media Geo-Tagged Photos

Citizen science characterization of meanings of toponyms of Kenya: a shared heritage

A quantitative analysis of global gazetteers: Patterns of coverage for common feature types

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