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A Novel and Integrated Semantic Recommendation System for E-Learning using Ontology

Published: 04 March 2016 Publication History

Abstract

As e-learning becomes increasingly popular among learners, the amount of course content on the Web also keeps expanding. Hence finding the most appropriate content for oneself has become a time-consuming task. Thus new systems which can efficiently recommend the most appropriate content to users based on their preferences are in demand. As a step towards providing the learners with such a system, we propose an ontology-based integrated recommendation system in the e-learning domain. Two ontologies viz. learner ontology and learning domain ontology are utilized to represent and model the knowledge about the learner and the learning domain respectively. In order to recommend the most appropriate content to users, our recommendation technique integrates four basic approaches: User profile matching, prerequisite learning path construction, collaborative filtering and semantic similarity technique. During their early phases, the recommender systems generally face the cold-start problem. This is because of the scarcity of information available during these phases. Our system successfully overcomes this problem by maintaining an ontological approach to user profiling. Our system also significantly improves the accuracy of recommendations, which we demonstrate experimentally.

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Cited By

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  • (2023)SCA Advice System: Ontology Framework for a Computer Curricula Advice System Based on Student BehaviorJournal of information and communication convergence engineering10.56977/jicce.2023.21.4.30621:4(306-315)Online publication date: 31-Dec-2023
  • (2021)A Literature Review on Intelligent Services Applied to Distance LearningEducation Sciences10.3390/educsci1111066611:11(666)Online publication date: 21-Oct-2021
  • (2018)Role of Ontology and Machine Learning in Recommender Systems2018 Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS)10.1109/EECCIS.2018.8692809(371-376)Online publication date: Oct-2018
  1. A Novel and Integrated Semantic Recommendation System for E-Learning using Ontology

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    cover image ACM Other conferences
    ICTCS '16: Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies
    March 2016
    843 pages
    ISBN:9781450339629
    DOI:10.1145/2905055
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 04 March 2016

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    Author Tags

    1. Cold-start problem
    2. Collaborative filtering
    3. E-learning
    4. Ontology
    5. Recommender system
    6. Semantic web
    7. User profiling

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    • (2023)SCA Advice System: Ontology Framework for a Computer Curricula Advice System Based on Student BehaviorJournal of information and communication convergence engineering10.56977/jicce.2023.21.4.30621:4(306-315)Online publication date: 31-Dec-2023
    • (2021)A Literature Review on Intelligent Services Applied to Distance LearningEducation Sciences10.3390/educsci1111066611:11(666)Online publication date: 21-Oct-2021
    • (2018)Role of Ontology and Machine Learning in Recommender Systems2018 Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS)10.1109/EECCIS.2018.8692809(371-376)Online publication date: Oct-2018

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