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Intelligent query optimization and course recommendation during online lectures in E-learning system

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Abstract

This article explores the possibility of disaggregating query/question information in e-learning system online lectures or course recommendations. Information arrangement includes reading, parsing and classification of inquiry/question messages. Data extraction is a kind of shallow content processing. It finds a set of predefined applicable content in the feature language archives and performs common language processing through artificial intelligence strategies. During online lectures, many problems emerged in the listener’s minds, and the development of query optimization systems is of great significance to the evaluation of problems in online lectures. The results shows that our proposed method improve the classification of action verbs to a more accurate level. Later, we evaluated our proposed method, and measured a very high macro average for all one-sixth of the cognitive domain. We also provide the analytical examination in which we compared the designed method with the state of the art methods. The results indicate that the proposed method outperform the traditional methods

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Authors and Affiliations

  1. School of Education, Guangzhou University, Guangzhou, 510006, People’s Republic of China

    Muhammad Sajid Rafiq

  2. School of Public Policy and Management, Guangzhou University, Guangzhou, 510006, People’s Republic of China

    Xie Jianshe

  3. School of Computer Science, Guangzhou University, Guangzhou, 510006, People’s Republic of China

    Muhammad Arif

  4. Department of Computer Science, University of Salerno, I-84084, Fisciano, SA, Italy

    Paola Barra

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  1. Muhammad Sajid Rafiq
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  2. Xie Jianshe
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  4. Paola Barra
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Correspondence to Xie Jianshe or Muhammad Arif.

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Rafiq, M.S., Jianshe, X., Arif, M. et al. Intelligent query optimization and course recommendation during online lectures in E-learning system. J Ambient Intell Human Comput 12, 10375–10394 (2021). https://doi.org/10.1007/s12652-020-02834-x

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