INFERÊNCIAS SEMÂNTICAS NA RECUPERAÇÃO DE INFORMAÇÕES PARA APLICAÇÕES HIPERMÍDIA / SEMANTIC INFERENCES IN INFORMATION RETRIEVAL FOR HYPERMEDIA APPLICATIONS

AUTOR(ES)
DATA DE PUBLICAÇÃO

2003

RESUMO

The information overload problem is one of the most challenging problems being faced today. In order to solve this problem, different areas such as Knowledge Management, Semantic Web and Hypermedia Applications Modeling have used similar solutions that consist basically of semantically structuring the information so it can be better accessed. This dissertation proposes an infrastructure based on classic algorithms and techniques of Artificial Intelligence that utilizes the increase in the availability of domain specific models to enable the applications where they are defined to make inferences about these particular domains. These inferences enable the creation of new functionalities in these applications. Four new functionalities were proposed and implemented, the most important being a semantic search. The new functionalities presented were successfully tested in two existing applications: the website of the Computer Science Department of PUC-Rio and the Portinari Knowledge Portal that presents all the work of the famous brazilian painter Candido Portinari.

ASSUNTO(S)

ontologies inferences data mining knowledge modeling algoritmos de propagacao de ativacao spread activation algorithms inferencias international marketing recuperacao de informacao mineracao de dados information retrieval marketing internacional ontologias aplicacoes hipermidia

ACESSO AO ARTIGO

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