Abstract
Aiming at the lack of individualization of current course resources in distance education, an intelligent recommendation model for distance education courses based on facial expression recognition is designed. Extract data that can represent the characteristics of the resource, such as title, subject, category, path, source, author, date, keywords, description information, etc., and represent the resource in the form of learning object metadata under the LOM specification. Use Reload Edtior 2.5.5 to edit metadata and package course content. Through the establishment of learning resource model, the structure of resources is more obvious, which is convenient for resource sharing and searching. Using the modeling method of requirement tree, the user requirement model is constructed based on ontology. Based on facial expression recognition, the framework of Intelligent Recommendation Model of distance education course is built, and the intelligent recommendation model of distance education course is constructed. Through comparative experiments, it is verified that the recommendation accuracy of Intelligent Recommendation Model Based on facial expression recognition is higher than the other two recommendation models, and it has high practicability.
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References
Cipryan, L., Plews, D.J., Ferretti, A., et al.: Effects of a 4-Week Very Low-Carbohydrate Diet on High-Intensity Interval Training Responses. J. Sports Sci. Med. 17(2), 259–268 (2018)
Laganà , P., Votano, L., Caruso, G., Azzaro, M., Lo Giudice, A., Delia, S.: Bacterial isolates from the Arctic region (Pasvik River, Norway): assessment of biofilm production and antibiotic susceptibility profiles. Environ. Sci. Pollut. Res. 25(2), 1089–1102 (2017). https://doi.org/10.1007/s11356-017-0485-1
Valentim, F.D.O., Oliveira, C.C., Amante, M.H.: Case for diagnosis. Primary cutaneous CD4+ small/medium T-cell lymphoproliferative disorder. Anais Brasileiros De Dermatologia, 94(1), 99–101 (2019)
Ruiz, G.J.C., Cunha Karen de Almeida Pinto Fernandes da, Silva M J R D , et al. Nasal-type extranodal T-cell/NK lymphoma in association with hemophagocytic syndrome. Anais Brasileiros De Dermatologia, 93(3), 422–425 (2018)
Tamar, H., Vianna, G.J.R., Hanifin, J.M.: New and developing therapies for atopic dermatitis. An. Bras. Dermatol. 93(1), 104–107 (2018)
Schwalbe, F.: The importance of student leagues on medical training in neurosurgery and residency choice. Arquivos Brasilros De Neurocirurgia Brazilian Neurosurgery 37(1), 13–18 (2018)
Peres, L.P., Oliveira, F.B., Cartell, A., et al.: Density of mast cells and intensity of pruritus in psoriasis vulgaris: a cross sectional study. Anais brasilros de dermatologia 93(3), 368–372 (2018)
Liu, S., Lu, M., Li, H., et al.: Prediction of gene expression patterns with generalized linear regression model. Front. Genet. 10, 120 (2019)
Liu, S., Li, Z., Zhang, Y., et al.: Introduction of key problems in long-distance learning and training. Mobile Netw. Appl. 24(1), 1–4 (2019)
Vincenti, G., Bucciero, A., Vaz de Carvalho, C. (eds.): eLEOT 2014. LNICSSITE, vol. 138. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-13293-8
Sundari, M.R., Shreya, G., Jawahar, T.: Course recommendation system. Int. J. Comput. Appl. 175(29), 13–16 (2020)
Thanh, D.T., Sang, L.H., Hai, N.T., et al.: Course recommendation with deep learning approach. Commun. Comput. Info. Sci. 1306, 63–77 (2020)
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By the Key Platform and Scientific Research Project of Guangdong Provincial Department of Education in 2017 - Youth Innovative Talents Project (Natural Science), Project No. 2017GkQNCX041.
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Yang, Y., Li, Dr., Huang, Xf., Wu, Sb. (2021). Intelligent Recommendation Model of Distance Education Courses Based on Facial Expression Recognition. In: Fu, W., Liu, S., Dai, J. (eds) e-Learning, e-Education, and Online Training. eLEOT 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 389. Springer, Cham. https://doi.org/10.1007/978-3-030-84383-0_12
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DOI: https://doi.org/10.1007/978-3-030-84383-0_12
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