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Autoria: • Fábio A. S. Silva
• Rosario Girardi
• Lucas Drumond
Título: An Information Retrieval Model for the Semantic Web
Complemento: Proceedings of the 6th International Conference on Information Technology : New Generations
Resumo: Exploring the metadata associated with documents in the Semantic Web is a way to increase the precision of information retrieval systems. Systems have been established so far failed to overcome fully the limitations of search based on keywords. Such systems are built from variations of classic models that represent information by keywords and work upon statistical correlations. This work proposes an information retrieval model to find information items with similar semantic content that a given user’s query. The information items internal representation is based on user interest groups, called “semantic cases”. The model also defines a similarity measure for ordering the results based on semantic distance between semantic cases items.
Palavras-chave: Information retrieval model; Semantic Web; Semantic case
Editora: IEEE
Local: Las Vegas, Nevada, USA
Data: 27 a 29 de abril de 2009
Meio: Anais de eventos
Vínculo: www.itng.info
Arquivo: final-itng.zip


Atualizado em 03/11/2016
UNIVERSIDADE FEDERAL DO MARANHÃO
CENTRO DE CIÊNCIAS EXATAS E TECNOLOGIA
DEPARTAMENTO DE INFORMÁTICA