de art culos cient cos seg un su grado de especicidad An approach to the recommendation of scientic articles according to their degree of specicity

on Abstract: This article presents a method for recommending scientic articles taking into consideration their degree of generality or specicity. This approach is based on the idea that less expert people in a specic topic prefer to read more general articles to be introduced into it, while people with more expertise prefer to read more specic articles. Compared to other recommendation techniques that focus on the analysis of user proles, our proposal is purely based on content analysis. We present two methods for recommending articles, based on Topic Modelling. The rst one is based on the divergence of topics given in the documents, while the second uses the similarities that exist between these topics. By using the proposed methods it was possible to determine the degree of specicity of an article, and the results obtained with them overcame those produced by an information retrieval traditional system.