Knowledge-Based Recommendation Systems: A Survey

被引：41

作者：

Bouraga, Sarah ^{[1
]}

Jureta, Ivan ^{[1
]}

Faulkner, Stephane ^{[1
]}

Herssens, Caroline ^{[1
]}

机构：

[1] Univ Namur, PReCISE Res Ctr, Dept Business Adm, Namur, Belgium

来源：

INTERNATIONAL JOURNAL OF INTELLIGENT INFORMATION TECHNOLOGIES | 2014年 / 10卷 / 02期

关键词：

Advice; Automation; Classification Framework; Decision-Making; Knowledge-Base System; Recommendation Problem; Recommendation System; User Profile;

D O I：

10.4018/ijiit.2014040101

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 [计算机科学与技术];

摘要：

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.

引用

页码：1 / 19

页数：19

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