A personalized recommender system for digital libraries
Giseli Rabello Lopes, Maria Aparecida M. Souto, Leandro Krug Wives, José Palazzo Moreira de Oliveira · 2008
This paper presents the evaluation of a Recommender System for scientific articles in digital libraries. This system is geared towards the Computer Science scientific community. Technologically speaking, the proposed system was developed under the Semantic Web perspective since it explores its emergent technologies such as the use of standard metadata for document description (i.e., Dublin Core), XML for user's profile description (i.e., Lattes Curriculum Vitae), and Web services and data providers (OAI) involved on the recommendations' generation process. The focus of this paper is the presentation and discussion of the extended experimental evaluation results obtained with a Web prototype.