Design and Development of Intelligent Learning System for University Innovation and Entrepreneurship Based on Knowledge Visualisation

Bibo Feng ()
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Bibo Feng: College of Computer Science and Engineering, Chongqing University of Technology, Chongqing 400054, P. R. China

Journal of Information & Knowledge Management (JIKM), 2024, vol. 23, issue 03, 1-17

Abstract: To build a comprehensive learning resource system covering learning process, learning users, learning resources and other aspects, an intelligent learning system for innovation and entrepreneurship in universities was constructed and designed combined with knowledge visualisation theory. The system includes student information record module, system recommendation calculation module, learning material module, and knowledge visualisation module. The research focuses on the system recommendation calculation module, including the User-based Collaborative Filtering Algorithm (UCF) and the Joint Recommendation (JR) algorithm of the application content recommendation algorithm. The best neighbour number of JR is 20, and the best transmission path length is 2. The recommendation effect is optimal under this setting. The convergence iterations of the training and test set of the joint recommendation algorithm are 80 times and 100 times, respectively. For the training set and test set, the accuracy, precision, sensitivity, recall, running time, error, and other performance evaluation indicators of the joint recommendation algorithm are better than the corresponding values of other recommendation algorithms. The system has a good design effect and experience effect in the application of the online learning platform.

Keywords: Knowledge visualisation; intelligent learning system; collaborative filtering algorithm; recommend (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0219649224500242

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