NDLI: Multi-model Ontology-Based Hybrid Recommender System in E-learning Domain

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Multi-model Ontology-Based Hybrid Recommender System in E-learning Domain

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Multi-model Ontology-Based Hybrid Recommender System in E-learning Domain

Content Provider	ACM Digital Library
Author	Romero, Elizabeth Nasraoui, Olfa Zhuhadar, Leyla Wyatt, Robert
Abstract	This paper introduces a multi-model ontology-based framework for semantic search of educational content in E-learning repository of courses, lectures, multimedia resources, etc. This hybrid recommender system is driven by two types of recommendations: content-based (domain ontology model) and rule-based (learner’s interest-based and cluster-based). The domain ontology is used to represent the learning materials. In this context, the ontology is composed by a hierarchy of concepts and sub-concepts. Whereas, the learner’s ontology model represents a subset of the domain ontology, and the cluster-based recommendations are added as additional semantic recommendations to the model. Combining the content-based with the rule-based provides the user with hybrid recommendations. All of them influenced the re-ranking of the retrieved documents with different weights. Our proposed approach has been implemented on the HyperManyMedia1 platform.
Starting Page	91
Ending Page	95
Page Count	5
File Format	PDF
ISBN	9780769538013
DOI	10.1109/WI-IAT.2009.238
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-09-15
Access Restriction	Subscribed
Subject Keyword	Recommender system personalization information retrieval ontology semantic
Content Type	Text
Resource Type	Article

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