Exploiting Text Mining Techniques for Contextual Recommendations
Marcos Aurélio Domingues, Camila Vaccari Sundermann, Marcelo Garcia Manzato, Ricardo Marcondes Marcacini, Solange Oliveira Rezende · 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) · 2014
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.