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|Título: ||Geospatial database generation from digital newspapers: use case for risk and disaster domains.|
|Autor: ||Preciado López, Julio César|
|Orientador: ||Berlanga Llavori, Rafael|
|Palavras-chave: ||Geographic information systems|
|Issue Date: ||3-Apr-2010|
|Relatório da Série N.º: ||Master of Science in Geospatial Technologies;TGEO0038|
|Resumo: ||The generation of geospatial databases is expensive in terms of time
and money. Many geospatial users still lack spatial data. Geographic
Information Extraction and Retrieval systems can alleviate this problem.
This work proposes a method to populate spatial databases automatically
from the Web. It applies the approach to the risk and disaster domain
taking digital newspapers as a data source. News stories on digital
newspapers contain rich thematic information that can be attached
to places. The use case of automating spatial database generation is
applied to Mexico using placenames. In Mexico, small and medium
disasters occur most years. The facts about these are frequently mentioned
in newspapers but rarely stored as records in national databases.
Therefore, it is difficult to estimate human and material losses of those
This work present two ways to extract information from digital news
using natural languages techniques for distilling the text, and the national
gazetteer codes to achieve placename-attribute disambiguation.
Two outputs are presented; a general one that exposes highly relevant
news, and another that attaches attributes of interest to placenames.
The later achieved a 75% rate of thematic relevance under qualitative
|Descrição: ||Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.|
|Appears in Collections:||NIMS - MSc Dissertations Geospatial Technologies (Erasmus-Mundus)|
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