Actas de congresos
Exploiting text mining techniques for contextual recommendations
Fecha
2014-08Registro en:
IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies, 2014, Warsaw.
9781479941438
Autor
Domingues, Marcos Aurelio
Sundermann, Camila Vaccari
Manzato, Marcelo Garcia
Marcacini, Ricardo Marcondes
Rezende, Solange Oliveira
Institución
Resumen
Unlike traditional recommender systems, which make recommendations only by using the relation between users and items, a context-aware recommender system makes recommendations by incorporating available contextual information into the recommendation process. One problem of context-aware approaches is that it is required techniques to extract such additional information in an automatic manner. In this paper, we propose to use two text mining techniques which are applied to textual data to infer contextual information automatically: named entities recognition and topic hierarchies. We evaluate the proposed technique in four context-aware recommender systems. The empirical results demonstrate that by using named entities and topic hierarchies we can provide better recommendations.