Invenire: um método evolucionário para combinar resultados das técnicas de sistemas de recomendação baseado em filtragem colaborativa
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Data
2014-08-20
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Universidade Federal de Goiás
Resumo
Recommendation 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.
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Citação
SILVA, 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.