AHP-GGAGR Based Innovative and Entrepreneurial Learning Platform for University Students
DOI:
https://doi.org/10.31449/inf.v48i19.6545Abstract
As the boost of the transformation of economy, innovation and entrepreneurship programs have become increasingly important in colleges and universities. Aiming at solving the problem that college students cannot obtain high-quality learning materials and related competition questions when they participate in innovation and entrepreneurship programs. The study firstly constructs the overall framework of the innovation and entrepreneurship platform for college students, and then constructs the cluster KAI model and the competition question model based on hierarchical analysis to portray the core disciplinary competence of college students and recommend the competition questions. Finally, a fusion gated graph-attention group competition topic recommendation model is proposed to complete the recommendation of competition topics and information such as materials by capturing the higher-order features of groups and competition topics. The results show that the research model starts to converge after 462 iterations and the convergence is stable. Meanwhile, when the recommendation list is 12, the model recommendation accuracy reaches 98.2%, and the AUC-ROC detection index is 0.865. It shows that the model constructed by the research has high accuracy and stability. The integration of the research model into the innovation and entrepreneurship learning platform for college students can greatly reduce the corresponding time of the platform, and the comprehensive satisfaction of college student users with the platform is above 85%. Through the platform constructed by the research, students can obtain relevant competition questions and learning resources more accurately, and the outcomes could also offer a theoretical basis for the construction of other platforms of the same type.翻译搜索复制References
Ogochukwu I J. Entrepreneurship innovation and finance. Journal of Behavioural Economics, Finance, Entrepreneurship, Accounting and Transport, 2021, 9(1):16-35.
Yu W, Wang S. Research on promoting factors of "Internet Plus Innovation and Entrepreneurship" based on the perspective of cloud analysis and fuzz analysis method. Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, 2021,40(4):8563-8568
Gao J, Yang L, Zou J, Fan X. Comparison of the influence of massive open online courses and traditional teaching methods in medical education in China: a meta-analysis. Biochemistry and Molecular Biology Education, 2021, 49(4):639-651.
Lotfi M, Asgharizadeh E, Hisam Omar A, Hosseinzadeh M Amoozad Mahdiraji H. Measuring Staff Satisfaction in Transportation System using AHP Method under Uncertainty. International Journal of Uncertainty, Fuzziness And Knowledge-Based Systems: IJUFKS, 2021, 29(6):875-889.
Amirali Salehi〢bari, Larson K. Group recommendation with noisy subjective preferences. Computational Intelligence, 2021, 1(37):210-225.
Qian Z, Zhou T. Construction of personalized learning platform based on intelligent algorithm in the context of industry education integration. Advances in multimedia, 2022,22(7), 1. 1-1. 14
Guan X, Fan Y, Qin Q, Deng K, Yang, G. Construction of science and technology achievement transfer and transformation platform based on deep learning and data mining technology. Journal of intelligent & fuzzy systems: applications in Engineering and Technology, 2020, 39(2 Pt. 1):1843-1854.
Li H. Construction of distance teaching platform based on mobile communication technology. International Journal of Networking and Virtual Organisations, 2019, 20(1):35-43
Cui Y, Zhang L, Hou Y, Tian G. Design of intelligent home pension service platform based on machine learning and wireless sensor network. Intelligent & Fuzzy Systems: applications in Engineering and Technology, 2021, 40(2):2529-2540.
Zan S, Zhang Y, Meng X, Lv P, Du Y. UDA: A user-difference attention for group recommendation. Information Sciences, 2021, 571(3):401-417.
Xiangguo Z, Zhen Z, Xin B, Yongjiao, S. A new point-of-interest group recommendation method in location-based social networks. Neural Computing & Amp; Applications, 2023,18(35):12945-12956.
Yaln E, Bilge A. A personality-based aggregation technique for group recommendation. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, 2020, 21(4):486-498.
Yang Q, Zhou S, Li H, Zhang, J. Embedding implicit user importance for group recommendation. Computers, Materials and Continua, 2020,3(64):1691- 1704.
Xu R, Zhang J. Research and implementation of remote mechanical fault diagnosis system based on B/S structure. Journal of Computational Methods in Sciences and Engineering, 2019, 19(8):1-7.
Bhattacharya P, Goyal P, Sarkar S. Using communities of words derived from multilingual word vectors for cross-language information retrieval in Indian languages. Acm Transactions on Asian Language Information Processing, 2019, 18(1):1. 1-1. 27.
Yu H, Ji Y, Li Q. Student sentiment classification model based on GRU neural network and TF-IDF algorithm. Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, 2021, 40(2):2301-2311.
Preethi P, Mamatha HR. Region-based convolutional neural network for segmenting text in epigraphical images. Artif. Intell. 2023, 1(2):119-127.
Choudhuri S, Adeniye S, Sen A. Distribution alignment using complement entropy objective and adaptive consensus-based label refinement for partial domain adaptation. Artificial Intelligence and Applications. 2023, 1(1): 43-51.
Downloads
Published
How to Cite
Issue
Section
License
I assign to Informatica, An International Journal of Computing and Informatics ("Journal") the copyright in the manuscript identified above and any additional material (figures, tables, illustrations, software or other information intended for publication) submitted as part of or as a supplement to the manuscript ("Paper") in all forms and media throughout the world, in all languages, for the full term of copyright, effective when and if the article is accepted for publication. This transfer includes the right to reproduce and/or to distribute the Paper to other journals or digital libraries in electronic and online forms and systems.
I understand that I retain the rights to use the pre-prints, off-prints, accepted manuscript and published journal Paper for personal use, scholarly purposes and internal institutional use.
In certain cases, I can ask for retaining the publishing rights of the Paper. The Journal can permit or deny the request for publishing rights, to which I fully agree.
I declare that the submitted Paper is original, has been written by the stated authors and has not been published elsewhere nor is currently being considered for publication by any other journal and will not be submitted for such review while under review by this Journal. The Paper contains no material that violates proprietary rights of any other person or entity. I have obtained written permission from copyright owners for any excerpts from copyrighted works that are included and have credited the sources in my article. I have informed the co-author(s) of the terms of this publishing agreement.
Copyright © Slovenian Society Informatika
