Título: | COMPARATIVE STUDY OF MOVIE RECOMMENDATION ALGORITHMS | ||||||||||||
Autor(es): |
PEDRO CHAMBERLAIN MATOS |
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Colaborador(es): |
MARCO SERPA MOLINARO - Orientador |
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Catalogação: | 03/MAR/2022 | Língua(s): | PORTUGUESE - BRAZIL |
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Tipo: | TEXT | Subtipo: | SENIOR PROJECT | ||||||||||
Notas: |
[pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio. [en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio. |
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Referência(s): |
[pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/TFCs/consultas/conteudo.php?strSecao=resultado&nrSeq=57546@1 [en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/TFCs/consultas/conteudo.php?strSecao=resultado&nrSeq=57546@2 |
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DOI: | https://doi.org/10.17771/PUCRio.acad.57546 | ||||||||||||
Resumo: | |||||||||||||
Personalized recommendations for series and movies are an important aspect of online
streaming services. This project s objective was to implement and evaluate a series of
algorithms used by movie recommendation systems. Four recommendation algorithms were
analyzed, two by method of collaborative filtering and two by method of content-based filtering.
In addition to the analysis of these, a new hybrid method was developed using two of the priorly
analyzed algorithms: a collaborative filtering algorithm based on matrix factorization by singular
value decomposition (SVD) and a content-based filtering algorithm using a similarity calculation
of textual information between movies. The new method was implemented and analyzed,
exhibiting better results than all previous methods. The evaluation data was based on movie
ratings given by users of the MovieLens social platform.
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