Knowledge-Based Recommendation Systems: A Survey

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...

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Vydané v:International journal of intelligent information technologies Ročník 10; číslo 2; s. 1 - 19
Hlavní autori: Bouraga, Sarah, Jureta, Ivan, Faulkner, Stéphane, Herssens, Caroline
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Hershey IGI Global 01.04.2014
Predmet:
Analysis
Automation
Classification
Filtering systems
Human
Knowledge
Knowledge base
Knowledge bases (artificial intelligence)
Knowledge-based systems
Recommender systems
Systems design
User profiles
United States
ISSN:1548-3657, 1548-3665
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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.
AbstractList 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.
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. Keywords: Advice, Automation, Classification Framework, Decision-Making, Knowledge-Base System, Recommendation Problem, Recommendation System, User Profile
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. Adapted from the source document.
Audience Academic
Author Faulkner, Stéphane
Jureta, Ivan
Herssens, Caroline
Bouraga, Sarah
AuthorAffiliation Department of Business Administration, PReCISE Research Center, University of Namur, Namur, Belgium
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  surname: Herssens
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  organization: Department of Business Administration, PReCISE Research Center, University of Namur, Namur, Belgium
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SubjectTerms Analysis
Automation
Classification
Filtering systems
Human
Knowledge
Knowledge base
Knowledge bases (artificial intelligence)
Knowledge-based systems
Recommender systems
Systems design
User profiles
Title Knowledge-Based Recommendation Systems: A Survey
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