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<p>The orientation programs in most of the schools do not mitigate the diverse necessities of students. In addition, the instability of the labor market and the complexity of life have a great impact on young people’s career choices. Faced with these concerns, high school students get confused when choosing a college major. Furthermore, the explosion of data on the Internet has caused most of the Internet users to make possible unsuitable decisions when browsing the Web, due to their inability to handle such large amounts of data. In this paper, the Case-based reasoning, and Ontology-based Hybrid Recommender System (COHRS) is proposed to assist high school students deciding the appropriate university/college, university major and career domain that best fit their preferences. COHRS uniquely combines case-based reasoning, collaborative filtering, knowledge base and ontology to explore the top N recommendations based on their fields of interest. The system has been evaluated on Lebanese students through a real-life dataset collected from different Lebanese cities. The first tests carried out on 60 high school students in Beirut city showed an average satisfaction level of 91.7% of the recommended results from the proposed system and 93.3% of them found the system very useful. The proposed system achieved an average accuracy level of 98% and 95% to retrieve the most similar cases and to extract appropriate recommendations respectively, which provides a very insightful capability to guide high school students in their future directions.</p>

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A case-based reasoning and ontology-based hybrid recommender system for student orientation in higher education

  • 期刊论文

  • 发表日期：

    2025年3月11日

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  • Christine Lahoud,
  • Sherin Moussa,
  • Charbel Obeid,
  • Hicham El Khoury

摘要

The orientation programs in most of the schools do not mitigate the diverse necessities of students. In addition, the instability of the labor market and the complexity of life have a great impact on young people’s career choices. Faced with these concerns, high school students get confused when choosing a college major. Furthermore, the explosion of data on the Internet has caused most of the Internet users to make possible unsuitable decisions when browsing the Web, due to their inability to handle such large amounts of data. In this paper, the Case-based reasoning, and Ontology-based Hybrid Recommender System (COHRS) is proposed to assist high school students deciding the appropriate university/college, university major and career domain that best fit their preferences. COHRS uniquely combines case-based reasoning, collaborative filtering, knowledge base and ontology to explore the top N recommendations based on their fields of interest. The system has been evaluated on Lebanese students through a real-life dataset collected from different Lebanese cities. The first tests carried out on 60 high school students in Beirut city showed an average satisfaction level of 91.7% of the recommended results from the proposed system and 93.3% of them found the system very useful. The proposed system achieved an average accuracy level of 98% and 95% to retrieve the most similar cases and to extract appropriate recommendations respectively, which provides a very insightful capability to guide high school students in their future directions.