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

Authors

Lucas Fernandes Brunialti, Universidade de São PauloFollow
Sarajane Marques Peres, Universidade de São PauloFollow
Valdinei Freire, Universidade de São PauloFollow
Clodoaldo Aparecido de Moraes Lima, Universidade de São PauloFollow

Document Type

Article

Publication Date

5-2015

Keywords

Content-Based Recommendation Systems, Textual Content, Machine Learning, Systematic Review

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.

Comments

This paper is in Portuguese (Aprendizado de Máquina em Sistemas de Recomendação Baseados em Conteúdo Textual: Uma Revisão Sistemática)

Recommended Citation

Brunialti, Lucas Fernandes; Peres, Sarajane Marques; Freire, Valdinei; and Lima, Clodoaldo Aparecido de Moraes, "Machine Learning in Textual Content-Based Recommendation Systems: A Systematic Review" (2015). Proceedings of the XI Brazilian Symposium on Information Systems (SBSI 2015). 73.
https://aisel.aisnet.org/sbis2015/73