Enriquecimento de dados de referência para recuperação de informação geográfica utilizando linked data

Detalhes bibliográficos
Ano de defesa: 2015
Autor(a) principal: Tiago Henrique Valadares Mendes de Moura
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Minas Gerais
UFMG
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/1843/ESBF-9XYHQL
Resumo: Gazetteers are instrumental in recognizing place names in documents such as Web pages, news, and social media messages. However, creating and maintaining gazetteers is still a complex and demanding task. We propose using Linked Data sources to put together gazetteer data that can be both broad (e.g. planetary) and deep (e.g., down to urban detail). Linked data sources also allow enriching the resulting gazetteer with a set of geographic and semantic relationships involving place names, other geographic and non-geographic terms, thus expanding the possibilities for solving typical GIR problems such as disambiguation and filtering. This work shows the results of efforts to compose and maintain an ontological gazetteer, in which places and their names are connected to other places and to non-geographic entities through geographic and semantic relationships. The objective of this proposal is to create, organize and populate a large ontological gazetteer with information obtained from the Web of Data, to be exposed as a Web service to applications and research initiatives on geographic information retrieval, text processing, named entity recognition and others. The resulting gazetteer contains more than 13 million places, extracted from the four datasets used in this work: GeoNames, Freebase, DBPedia and LinkedGeoData. In addition, we present an analysis of how the datasets overlap one another.