Bringing knowledge into recommender systems

Authors:
Jose A. Rodrigues Nt;Luiz Fernando Cardoso Tomaz;Jano Moreira De Souza;Geraldo XexéO
Affiliations:
COPPE - Universidade Federal do Rio de Janeiro, Programa de Engenharia de Sistemas e Computação, Caixa Postal 68.511, CEP 21941-972, Rio de Janeiro, RJ, Brazil;COPPE - Universidade Federal do Rio de Janeiro, Programa de Engenharia de Sistemas e Computação, Caixa Postal 68.511, CEP 21941-972, Rio de Janeiro, RJ, Brazil;COPPE - Universidade Federal do Rio de Janeiro, Programa de Engenharia de Sistemas e Computação, Caixa Postal 68.511, CEP 21941-972, Rio de Janeiro, RJ, Brazil;COPPE - Universidade Federal do Rio de Janeiro, Programa de Engenharia de Sistemas e Computação, Caixa Postal 68.511, CEP 21941-972, Rio de Janeiro, RJ, Brazil
Venue:
Journal of Systems and Software
Year:
2013

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Abstract

Recommender systems are largely used nowadays to support collaborative tasks. However, it is important to consider each user's knowledge of the system for the recommended subject. In this paper we describe the use of user knowledge to improve the recommender system of the Business Process Cooperative Editor (BPCE), a collaborative business process modeling tool. We use the concept of the Knowledge Vector, developed in a previous work on collaborative navigation, to factor user knowledge into recommendations. We present Knowledge Vectors and how they are applied to the editor. A simulation to evaluate the effectiveness of the editor's new recommender system is presented.