Semantic Web Recommender System Based Personalization Service for User XQuery Pattern

2005 ◽  
pp. 848-857 ◽  
Author(s):  
JinHong Kim ◽  
EunSeok Lee
Keyword(s):  
Semantic Web ◽  
Recommender System

scholarly journals Ontology and Rule-Based Recommender System for E-learning Applications

2019 ◽  
Vol 14 (15) ◽  
pp. 4 ◽  
Author(s):  
Bouchra Bouihi ◽  
Mohamed Bahaj
Keyword(s):  
Semantic Web ◽  
Recommender System ◽  
Web Application ◽  
Domain Knowledge ◽  
Recommendation System ◽  
Learning Performance ◽  
Learning Context ◽  
Learning Materials ◽  
Continuous Growth ◽  
Application Architecture

The continuous growth of the internet has given rise to an overwhelming mass of learning materials. Which has increased the demand for a recommendation system to filter information and to deliver the learning materials that fit learners learning context. In this paper, we propose an architecture of a semantic web based recommender system. The proposed architecture is a redesigned architecture of the classical 3-tiers web application architecture with an additional semantic layer. This layer holds two semantic subsystems: an Ontology-based subsystem and SWRL (Semantic Web Rule Language) rules one. The Ontology subsystem is used as a reusable and sharable domain knowledge to model the learning content and context. The SWRL rules are used as a recommendation and filtering technique based on learning object relevance and weighting. These rules are organized into four categories: Learning History Rules (LHR), Learning Performance Rules (LPR), Learning Social Network Rules (LSNR) and Learning Pathway Rules (PR).

Semantic Web Technologies for e-Learning: Models and Implementation

Informatica ◽  
2015 ◽  
Vol 26 (2) ◽  
pp. 221-240 ◽  
Author(s):  
Valentina Dagienė ◽  
Daina Gudonienė ◽  
Renata Burbaitė
Keyword(s):  
Semantic Web ◽  
Learning Models ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
E Learning
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