Uma aplicação de mineração de dados para recomendação social

• Ano de defesa: 2013
• Autor(a) principal: FEITOSA, Rodrigo Miranda
• Orientador(a): LABIDI, Sofiane
• 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: DEPARTAMENTO DE ENGENHARIA DA ELETRICIDADE/CCET
• País: Brasil
• Palavras-chave em Português: Mineração de Dados; Rede Social Baseada em Localização e Recomendação Socia; Sistemas de Recomendação; Data Mining; Recommender Systems; Location-Based Social Networking and Social Recommendation
• Área do conhecimento CNPq: Sistemas de Informação
• Link de acesso: http://tedebc.ufma.br:8080/jspui/handle/tede/1832

The search of knowledge and its manipulation in companies, institutions or other organizations has become a challenge nowadays. Mostly due to two aspects: the large volume of information available and the difficulty in extracting the knowledge proper to each person (intellectual capital). This difficulty becomes more accentuated when the scenario involved the extraction of knowledge is the Web. The area of Knowledge Management seeks a solution to the limitations described above. Techniques for extracting and control of knowledge can be adopted with the use of Artificial Intelligence, particularly the Knowledge Discovery in Databases. This work proposes the creation of a methodology and application that perform the Data Mining with textual information linked to geo data in a social network, in order to promote Social Recommendation. However, approaches in building recommendation systems present some shortcomings in filtering the results and the way they are suggested to users. The research aims to remedy these deficiencies and addresses issues that still need to search more effective and consolidated results.