Seleção e geração de características utilizando regras de associação para o problema de ordenação de resultados de máquinas de buscas

• Autor(a) principal: Araujo, Carina Calixto Ribeiro de
• Data de Publicação: 2014
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• dARK ID: ark:/38995/0013000006t4w
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/4404
• topic: Recuperação da informação; Learning to rank; Regras de associação; Information retrieval; Learning to rank; Assossiation rules; CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO

Information Retrieval is an area of IT that deals with document storage and the information retrieval in these documents. With the advent of the Internet, the number of documents produced has increased as well as the need to retrieve the information more accurately. Many approaches have been proposed to meet these requirements and one of them is Learning to rank (L2R). Despite major advances achieved in the accuracy of retrived documents, there is still considerable room for improvement. This master thesis proposes the use of feature selection and generation using association rules to improve the accuracy of the L2R methods.