2014-12-222014-08-20SILVA, Edjalma Queiroz da. Invenire: um método evolucionário para combinar resultados das técnicas de sistemas de recomendação baseado em filtragem colaborativa. 2014. 154 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2014.http://repositorio.bc.ufg.br/tede/handle/tede/3818Recommendation systems function as a guide, helping users to discover products of interest. There are various techniques and approaches in the literature that enable the generationofrecommendations.Thisisinterestingbecauseitemphasizesthediversityof options;ontheotherhand,itcancausedoubtthesystemdesigneraboutwhichisthebest techniquetouse.Eachoftheseapproacheshasparticularitiesanddependsonthecontext to be applied. Therefore, the decision to choose between the techniques is complex to be done manually. This work proposes an evolutionary approach for combining results of recommendation techniques (Invenire) in order to automate the choice of techniques and get fewer errors in recommendations. To evaluate the proposal, experiments were performed with a dataset from MovieLens and some Collaborative Filtering techniques. The results show that the combining methodology proposed in this paper performs better than any one collaborative filtering technique separately in the context addressed. The improvement varies from 3,6% to 118,99% depending on the technique and the experiment executed.application/pdfAcesso AbertoSistemas de recomendaçãoFiltragem colaborativaCombinar resultadosSimilaridade eInvenireRecommender systemsCollaborative filteringCombining resultsSimilarityCIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAODissertação