Machine Learning in Textual Content-based Recommendation Systems: A Systematic Review

Sun 14 June 2015

Some days ago I presented a paper (systematic review) in SBSI 2015 conference (XI Brazilian Symposium on Information System).

Considerations

  • First I want to thanks the staff from SBSI 2015 (Simpósio Brasileiro de Sistemas de Informação - Brazillian Symposium of Information Systems) and SBC (Sociedade Brasileira de Computação - Brazillian Society of Computation) for having my paper published. The bibtex reference is the following:
  • Also thanks to my advisor Professor Sarajane Marques Peres, my co-advisor Professor Valdinei Freire and professor Clodoaldo Lima for helping in the review and in the paper.

Citing:

@inproceedings{ Brunialti2015,
    author="Lucas Brunialti and Sarajane Peres and Valdinei Freire and Clodoaldo Lima",
    title="Aprendizado de Máquina em Sistemas de Recomendação baseados em conteúdo textual: uma Revisão Sistemática",
    booktitle="SBSI 2015: Main Track",
    address="Goiânia-GO, Brazil",
    days="26-29",
    moths="may",
    year="2015"
}

Abstract

Content-based Recommendation Systems (CbRS) is a research area in which Machine Learning (ML) strategies can be applied with success. However, specifically in textual CbRS, the use of ML has not been expressive in recent years. To contribute to the evolution of the intersection of such areas, we present a Systematic Review to identify, interpret and evaluate how the ML strategies have been applied to CbRS.

The paper is available in portuguese here (page 203).