DESENVOLVIMENTO DE UMA FAMÍLIA DE SISTEMAS DE RECOMENDAÇÕES BASEADOS NA TECNOLOGIA DA WEB SEMÂNTICA E SEU REUSO NA RECOMENDAÇÃO DE INSTRUMENTOS JURÍDICO-TRIBUTÁRIOS

• Ano de defesa: 2008
• Autor(a) principal: Mariano, Roberval Gomes
• Orientador(a): GIRARDI, Rosario
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Maranhão
• Programa de Pós-Graduação: PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA DE ELETRICIDADE/CCET
• Departamento: Engenharia
• País: BR
• Palavras-chave em Português: Sistema de recomendações; Reuso; Web Semântica; filtragem de Informação; Ontologia Tributária; Engenharia de Domínio Multiagente; Engenharia de Aplicação Multiagente
• Palavras-chave em Inglês: Recommender Systems; Reuse; Semantic Web; Information Filtering; Tributary Ontology; Multi-agent Domain Engineering; Multi-agent Application Engineering
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::METODOLOGIA E TECNICAS DA COMPUTACAO::SISTEMAS DE INFORMACAO
• Link de acesso: http://tedebc.ufma.br:8080/jspui/handle/tede/400

The huge amount of data available on the Web and its dynamic nature create a demand for information filtering applications such as recommender systems. The lack of semantic structure of data available on the Web constitutes a barrier for increasing the effectiveness of such applications family. This work discusses the analysis, design, implementation and evaluation of Semantic Web based hybrid filtering agents. Such agents were integrated in ONTOSERS, an application family for the development of recommender systems based on the Semantic Web technology. The implemented agents were evaluated and their results were compared with the results of collaborative and content-based filtering agents. The hybrid filtering techniques presented better results than the other approaches in the conducted experiments. The tested hybrid filtering approaches were the weighted and switched ones. The explicit feedback was used to validate the recommendations, presenting a better correlation with the hybrid filtering techniques. The developed agents were also evaluated through the reuse of the ONTOSERS systems family, a multi-agent recommender system in the Brazilian tributary domain.