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Conference Papers Year : 2024

Neuro-symbolic Approach to Extracting Knowledge from Learners' Evaluation Results

Abstract

Neural systems provide advanced learning capability and intelligent perception but lack efficient reasoning, while symbolic systems are known for cognitive intelligence. In recent years, the neuro-symbolic approach has experienced a renaissance of interest with the introduction of new frameworks and algorithms in a variety of practical applications. This approach is based on the classical neurological problem-solving and reasoning and combines neural and symbolic approaches to leverage their respective advantages. The neuro-symbolic approach has been widely utilized in diverse domains such as recommender systems, information retrieval, healthcare, and finance. However, despite its rapid development, it is not yet fully exploited in the field of education. This article focuses on the application of neuro-symbolic techniques in the field of education with the aim of enhancing vocational guidance through the extraction of knowledge from evaluation results.
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Dates and versions

hal-04549490 , version 1 (17-04-2024)

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  • HAL Id : hal-04549490 , version 1

Cite

Amoura Zahoua, Farida Bouarab, Samia Lazib, Fatiha Tali. Neuro-symbolic Approach to Extracting Knowledge from Learners' Evaluation Results. The Second International Conference on Big Data, IoT, Web Intelligence, and Applications, Université de Bejaia-Algérie, Nov 2024, Bejaia, Algeria. ⟨hal-04549490⟩
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