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.
| Original language | English |
|---|---|
| Pages (from-to) | 1-19 |
| Number of pages | 19 |
| Journal | International Journal of Intelligent Information Technologies |
| Volume | 10 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Jan 2014 |
Keywords
- Advice
- Automation
- Classification framework
- Decision-Making
- Knowledge-Base system
- Recommendation problem
- Recommendation system
- User profile
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Dive into the research topics of 'Knowledge-based recommendation systems: A survey'. Together they form a unique fingerprint.Student theses
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The Design of an Online Social Network and its Knowledge-Based Recommendation System
Bouraga, S. (Author)Faulkner, S. (Supervisor), Jureta, I. (Supervisor), Castiaux, A. (President), Mouratidis, H. (Jury), Perini, A. (Jury), Kolp, M. (Jury) & Petit, M. (Jury), 21 Apr 2017Student thesis: Doc types › Doctor of Sciences