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Knowledge-Based Recommendation Systems: A Survey

Sarah Bouraga, Ivan Jureta, Stéphane Faulkner, Caroline Herssens

Source Title: International Journal of Intelligent Information Technologies (IJIIT)10(2)

ISSN: 1548-3657|EISSN: 1548-3665|EISBN13: 9781466654808|DOI: 10.4018/ijiit.2014040101

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MLA

Bouraga, Sarah, et al. "Knowledge-Based Recommendation Systems: A Survey." IJIIT vol.10, no.2 2014: pp.1-19. http://doi.org/10.4018/ijiit.2014040101

APA

Bouraga, S., Jureta, I., Faulkner, S., & Herssens, C. (2014). Knowledge-Based Recommendation Systems: A Survey. International Journal of Intelligent Information Technologies (IJIIT), 10(2), 1-19. http://doi.org/10.4018/ijiit.2014040101

Chicago

Bouraga, Sarah, et al. "Knowledge-Based Recommendation Systems: A Survey," International Journal of Intelligent Information Technologies (IJIIT) 10, no.2: 1-19. http://doi.org/10.4018/ijiit.2014040101

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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.

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Knowledge-Based Recommendation Systems: A Survey

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