Knowledge-Based Recommendation Systems: A Survey

Sarah Bouraga, Ivan Jureta, Stéphane Faulkner and Caroline Herssens
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Sarah Bouraga: Department of Business Administration, PReCISE Research Center, University of Namur, Namur, Belgium
Ivan Jureta: Department of Business Administration, PReCISE Research Center, University of Namur, Namur, Belgium
Stéphane Faulkner: Department of Business Administration, PReCISE Research Center, University of Namur, Namur, Belgium
Caroline Herssens: Department of Business Administration, PReCISE Research Center, University of Namur, Namur, Belgium

International Journal of Intelligent Information Technologies (IJIIT), 2014, vol. 10, issue 2, 1-19

Abstract: Knowledge-Base Recommendation (or Recommender) Systems (KBRS) provide the user with advice about a decision to make or an action to take. KBRS rely on knowledge provided by human experts, encoded in the system and applied to input data, in order to generate recommendations. This survey overviews the main ideas characterizing a KBRS. Using a classification framework, the survey overviews KBRS components, user problems for which recommendations are given, knowledge content of the system, and the degree of automation in producing recommendations.

Date: 2014
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