User Recommender System Based on Knowledge, Availability, and Reputation From Interactions in Forums

SILVANA ACIAR; GABRIELA ACIAR; CESAR COLLAZO; CARINA GONZALEZ

IEEE Revista Iberoamericana de Tecnologias del Aprendizaje

IEEE-RITA

Año: 2016

1932-8540

In this paper, a recommender system is described, where the user recommendations are made considering the degree of knowledge and user availability to answer questions from other users. A new approach to make the recommendations is added to the system: the reputation of the candidate users in the community. The reputation is calculated on the basis of past interactions, more precisely the satisfaction of the user who made the question. Results show that the recommendations based on reputation, knowledge, and availability of users are more accurate