Extracting Geographic Context from the Web: GeoReferencing in MyMoSe

Zubizarreta, Álvaro; Fuente, Pablo de la; Cantera, José M.; Arias, Mario Lobo; Cabrero, Jorge; García, Guido; Llamas, César; Vegas, Jesús

doi:10.1007/978-3-642-00958-7_50

Cited by 7 publications

(3 citation statements)

References 9 publications

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“…Much research has been carried out to extract geospatial information from different text contents, such as web queries, micro-text messages, metadata and Wikipedia entries [8][9][10][11][12], and some research such as [13] has been conducted on retrieving temporal information from text documents. Our effort focuses on introducing geospatial or temporal information extraction methods from relatively structured text contents.…”

Section: Geospatial Information Extraction From the Web And Text Documentioning

confidence: 99%

Spatiotemporal Information Extraction from a Historic Expedition Gazetteer

Bekele

Singh³

2016

Preprint

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Historic expeditions are events that are flavored by exploratory, scientific, military or geographic characteristics. Such events are often documented in literature, journey notes or personal diaries. A typical historic expedition involves multiple site visits and their descriptions contain spatiotemporal and attributive contexts. Expeditions involve movements in space that can be represented by triplet features (location, time and description). However, such features are implicit and innate parts of textual documents. Extracting the geospatial information from these documents requires understanding the contextualized entities in the text. To this end, we developed a semi-automated framework that has multiple Information Retrieval and Natural Language Processing components to extract the spatiotemporal information from a two-volumes historic expedition gazetteer. Our framework has three basic components, namely, the Text Preprocessor, the Gazetteer Processing Machine and the JAPE (Java Annotation Pattern Engine) Transducer. We used the Brazilian Ornithological Gazetteer as an experimental dataset and extracted the spatial and temporal entities from entries that refer to three expeditioners' site visits and mapped the trajectory of each expedition using the extracted information. Finally, one of the mapped trajectories was manually compared with a historical reference map of that expedition to assess the reliability of our framework. The reference map was manually prepared in previous research work by others.

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Section: Geospatial Information Extraction From the Web And Text Documentioning

confidence: 99%

Spatiotemporal Information Extraction from a Historic Expedition Gazetteer

Bekele

Singh³

2016

Preprint

View full text Add to dashboard Cite

show abstract

“…Much research has been carried out to extract geospatial information from different text contents, such as web queries, micro-text messages, metadata and Wikipedia entries [8][9][10][11][12], and some research [13] has been conducted on retrieving temporal information from text documents. Our effort focuses on introducing geospatial or temporal information extraction methods from relatively structured text contents.…”

Section: Geospatial Information Extraction From the Web And Text Documentioning

confidence: 99%

Spatiotemporal Information Extraction from a Historic Expedition Gazetteer

Bekele

Singh³

2016

IJGI

View full text Add to dashboard Cite

Historic expeditions are events that are flavored by exploratory, scientific, military or geographic characteristics. Such events are often documented in literature, journey notes or personal diaries. A typical historic expedition involves multiple site visits and their descriptions contain spatiotemporal and attributive contexts. Expeditions involve movements in space that can be represented by triplet features (location, time and description). However, such features are implicit and innate parts of textual documents. Extracting the geospatial information from these documents requires understanding the contextualized entities in the text. To this end, we developed a semi-automated framework that has multiple Information Retrieval and Natural Language Processing components to extract the spatiotemporal information from a two-volume historic expedition gazetteer. Our framework has three basic components, namely, the Text Preprocessor, the Gazetteer Processing Machine and the JAPE (Java Annotation Pattern Engine) Transducer. We used the Brazilian Ornithological Gazetteer as an experimental dataset and extracted the spatial and temporal entities from entries that refer to three expeditioners' site visits (which took place between 1910 and 1926) and mapped the trajectory of each expedition using the extracted information. Finally, one of the mapped trajectories was manually compared with a historical reference map of that expedition to assess the reliability of our framework.

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“…The literature divides geoparsing in three parts: (1) Parsing a textual document and identifying geographic references, (2) resolving the ambiguity and (3) finding the relevant scope. A common way to identify all geographic references (geotags) is to cross-check the input with a gazetteer [27]. A gazetteer is a database that stores information about places and the connections between them.…”

Section: Related Workmentioning

confidence: 99%

Toward location-aware Web: extraction method, applications and evaluation

Hess

Magagna

Sutanto

2013

Pers Ubiquit Comput

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Location-based services (LBS) belong to one of the most popular types of services today. However, a recurring issue is that most of the content in LBS has to be created from scratch and needs to be explicitly tagged to locations, which makes existing Web content not directly usable for LBS. In this paper, we aim at making Web sites location-aware and feed this information to LBS. Our approach toward location-aware Web is threefold: First, we present a location extraction method: SALT. It receives Web sites as input and equips them with location tags. Compared to other approaches, SALT is capable of extracting locations with a precision up to the street level. Performance evaluations further show high applicability for practice. Second, we present three applications for SALT: Webnear.me, Local Browsing and Local Facebook. Webnear.me offers location-aware Web surfing through a mobile Web site and a smartphone app. Local Browsing adds the feature to browse by nearby tags, extracted from Web sites delivered by SALT. Local Facebook extends location tagging to social networks, allowing to run SALT on one's own and one's friends' timeline. Finally, we evaluate SALT for technology acceptance of Webnear.me through a formative user study. Through real user data, collected during a 3 months pilot field deployment of Webnear.me, we assess whether SALT is a proper instance of ''location of a Web site''.

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Extracting Geographic Context from the Web: GeoReferencing in MyMoSe

Cited by 7 publications

References 9 publications

Spatiotemporal Information Extraction from a Historic Expedition Gazetteer

Spatiotemporal Information Extraction from a Historic Expedition Gazetteer

Spatiotemporal Information Extraction from a Historic Expedition Gazetteer

Toward location-aware Web: extraction method, applications and evaluation

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