The Role of Gazetteers in Geographic Knowledge Discovery on the Web

Souza, Ligiane A. de; Davis, Clodoveu A.; Borges, Karla A. V.; Delboni, Tiago M.; Laender, Alberto H. F.

doi:10.1109/laweb.2005.38

Cited by 26 publications

(19 citation statements)

References 12 publications

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“…Souza et al collected local references for Brazil from a national mapping agency [30], the postal company and some local government institutions, but even that was insufficient, so they included tourist websites.…”

Section: Our Research Questionsmentioning

confidence: 99%

Automatic gazetteer enrichment with user-geocoded data

Gelernter

Ganesh

Krishnakumar

et al. 2013

Proceedings of the Second ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information

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Geographical knowledge resources or gazetteers that are enriched with local information have the potential to add geographic precision to information retrieval. We have identified sources of novel local gazetteer entries in crowd-sourced OpenStreetMap and Wikimapia geotags that include geo-coordinates. We created a fuzzy match algorithm using machine learning (SVM) that checks both for approximate spelling and approximate geocoding in order to find duplicates between the crowd-sourced tags and the gazetteer in effort to absorb those tags that are novel. For each crowd-sourced tag, our algorithm generates candidate matches from the gazetteer and then ranks those candidates based on word form or geographical relations between each tag and gazetteer candidate. We compared a baseline of edit distance for candidate ranking to an SVM-trained candidate ranking model on a city level location tag match task. Experiment results show that the SVM greatly outperforms the baseline.

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Section: Our Research Questionsmentioning

confidence: 99%

Automatic gazetteer enrichment with user-geocoded data

Gelernter

Ganesh

Krishnakumar

et al. 2013

Proceedings of the Second ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information

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“…A good example is GeoWordNet 9 (georeferenced version of WordNet 10 ) which is an integrated system of GeoNames with WordNet plus the Italian section of MultiWordNet 11 (Giunchiglia et al, 2010, Buscaldi andRosso, 2009). Gazetteers are widely used in Geospatial Information Retrieval (GIR) research (Borges et al, 2011, Amitay et al, 2004, Hill, 2000, Souza et al, 2005 but it is mostly argued that they are not fully supported in this sense as there are structural limitations and lack of intra-urban place names, no records on spatial relationships among elements other than relying on their proximity based footprints (Machado et al, 2011). Automatic recognition of geographic characteristics from web contents remain challenging and numerous approaches like automatic indexing and georeferencing (Larson, 1996), ontology-driven approaches (Jones et al, 2001, Fu et al, 2005a, semantic query expansion (Delboni et al, 2007, Fu et al, 2005b and natural language positioning (Delboni et al, 2007) along with gazetteers and geocoding techniques are proposed (Borges et al, 2011).…”

Section: Gir Gazetteers and Ontologiesmentioning

confidence: 99%

“…An ontology schema (Figure 3) was designed for Queensland Gazetteer based on OMT-G Gazetteer conceptual schema (Souza et al, 2005) and OnLocus simplified schema (Borges et al, 2011). Ontology design and development: Ontologies are key in semantic information processing.…”

Section: The Research Approachmentioning

confidence: 99%

Semantic Location Extraction From Crowdsourced Data

Koswatte¹,

McDougall²,

Liu³

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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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.

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“…The recognition and manipulation of place names, which can function as a special set of keywords, is also critical for GIR. For that purpose, gazetteers (dictionaries of place names) are often used [23,42].…”

Section: Related Workmentioning

confidence: 99%

“…The approach is based on an ontology that has been designed to facilitate the process of recognizing, extracting, and geocoding partial or complete references to places embedded in text. It combines the extraction ontology approach described earlier with advances on urban gazetteers [42] created from data available on the Web and geocoding techniques [11]. This ontology, called OnLocus, is described in Section 4.…”

Section: Related Workmentioning

confidence: 99%

Ontology-driven discovery of geospatial evidence in web pages

et al. 2010

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When users need to find something on the Web that is related to a place, chances are place names will be submitted along with some other keywords to a search engine. However, automatic recognition of geographic characteristics embedded in Web documents, which would allow for a better connection between documents and places, remains a difficult task. We propose an ontology-driven approach to facilitate the process of recognizing, extracting, and geocoding partial or complete references to places embedded in text. Our approach combines an extraction ontology with urban gazetteers and geocoding techniques. This ontology, called OnLocus, is used to guide the discovery of geospatial evidence from the contents of Web pages. We show that addresses and positioning expressions, along with fragments such as postal codes or telephone area codes, provide satisfactory support for local search applications, since they are able to determine approximations to the physical location of services and activities named within Web pages. Our experiments show the feasibility of performing automated address extraction and geocoding to identify locations associated to Web pages. Combining location identifiers with basic addresses improved the precision of extractions and reduced the number of false positive results. Geoinformatica (2011) 15:609-631

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The Role of Gazetteers in Geographic Knowledge Discovery on the Web

Cited by 26 publications

References 12 publications

Automatic gazetteer enrichment with user-geocoded data

Automatic gazetteer enrichment with user-geocoded data

Semantic Location Extraction From Crowdsourced Data

Ontology-driven discovery of geospatial evidence in web pages

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