참고문헌
- K. Lee and E. Park, "The Study of the System Development on the Safe Environment of Children's Smartphone Use and Contents Recommendations", Journal of Digital Contents Society , Vol. 19 No. 5, pp. 845-852, 2018. https://doi.org/10.9728/dcs.2018.19.5.845
- B. Gupta, M. Goul, and B. Dinter, "Business Intelligence and Big Data in Higher Education: Status of a Multi-Year Model Curriculum Development Effort for Business School Undergraduates, MS Graduates, and MBAs", Journal of CAIS, Vol. 36, No. 23, pp. 449-476, 2015.
- Nationl Youth Policy Institute, 1st 7th Survey Data User's guide in Korea Children and Youth Paner Survey(KCYPS), National Youth Policy Institute, Seoul, 2017.
- S. Lee and Y. Lee, "An Analysis of Annual Changes on the Determining Factors Multicultural Acceptability for Using Data Mining", Korean Journal of Youth Studies, Vol. 24, No. 4, pp. 1-26, 2017.
- M. Lee, "Analysis of Predictive Factors of School Violence Behavior and Its Solution Using Neural Network Analysis", Korean Journal of Association for Learner centered Curriculum and Instruction, Vol. 17 No. 22, pp. 537-561, 2017.
- K. Jung and W. Jeong, "Identifying Latent Classes in Children's School Adjustment Using the Cluster Analysis and Testing Eco-system Variables as Predictors of Latent Classes", Korean Journal of Forum for youth culture, Vol. 32, pp. 119-143, 2012.
- K. Lee, M. Lee, and Y. Kim, "Research on blog search technique using Kmeans", The Proceeding of Korea Intelligent Information Systems Society - The Fall Conference, pp. 269-275, 2009.
- M. Arif, "Application of Data Mining Using Artificial Neural Network : Survey", International Journal of Database Theory and Application, Vol. 8 No. 1, pp.245-270, 2015.
- M. Chen, S. Mao, and Y. Liu, "Big Data: A Survey", Journal of Mobile Networks and Applications, Vol. 19, No. 2, pp 171-209, 2014. https://doi.org/10.1007/s11036-013-0489-0
- Soo Jung Lee, "Performance Analysis of Similarity Reflecting Jaccard Index for Solving Data Sparsity in Collaborative Filtering", Journal of Computer Education, Vol. 19, No. 4, pp. 59-66, 2016.
- S. Kwon, S. Kim, O. Tak, and H. Jeong, "A Study on the Clustering Method of Row and Multiplex Housing in Seoul Using Kmeans Clustering Algorithm and Hedonic Model", Journal of Intelligence and Information System, Vol. 23, No. 3, pp. 95-118, 2017. https://doi.org/10.13088/jiis.2017.23.1.095
- Kabacoff Robert, R in Action-Data analysis and graphics with R, Oreilly&AssociatesInc, 2015.
- J. Herlocker, J. A. Konstan, and J. Riedl, "An Empirical Analysis of Design Choices in Neighborhood-Based Collaborative Filtering Algorithms", Information Retrieval, Vol. 5, No. 4, pp. 287-310, 2002. https://doi.org/10.1023/A:1020443909834
- Kwang-Sung Jun, Kyu-Baek Hwang, "An Efficient Collaborative Filtering Method Based on k-Nearest Neighbor Learning for Large-Scale Data", Korea Information Science Society, Vol. 35(1C), pp. 376-380, 2008.
- M. Khoshneshin and W. Nick Street "Collaborative filtering via euclidean, embedding", The Proceedings of the fourth ACM conference on Recommender systems, pp. 87-94, 2010.
- Jun Wang, Arjen P. De Vries, and Marcel J. T. Reinders, "Unifying user-based and item-based collaborative filtering approaches by similarity fusion", In SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, 2006.
- T. Chai and R. R. Draxler, "Root mean square error (RMSE) or mean absolute error (MAE)? - Arguments against avoiding RMSE in the literature", Geoscientific Model Development, Vol. 7, No. 3, pp. 1247-1250, 2014. https://doi.org/10.5194/gmd-7-1247-2014
피인용 문헌
- Analysis of Core Concepts in Problem Solving and Programming Unit of Informatics Subject Textbooks in Middle School Revised in 2015 vol.21, pp.1, 2018, https://doi.org/10.9728/dcs.2020.21.1.63
- COVID-19 Pandemic and Investor Herding Behavior vol.22, pp.7, 2021, https://doi.org/10.9728/dcs.2021.22.7.1083