References
- Abu Saa, A, Al-Emran, M and Shaalan, K. 2019. Factors affecting students’ performance in higher education: a systematic review of predictive data mining techniques. Technology, Knowledge and Learning, 24(4): 567–598. DOI: 10.1007/s10758-019-09408-7
- Alguliyev, RM, Aliguliyev, RM and Sukhostat, LV. 2020. Efficient algorithm for big data clustering on single machine. CAAI Transactions on Intelligence Technology, 5(1): 9–14. DOI: 10.1049/trit.2019.0048
- Bağdatli, MEC and Dokuz, AŞ. 2021. Modeling discretionary lane-changing decisions using an improved fuzzy cognitive map with association rule mining. Transportation letters, 13(8): 623–633. DOI: 10.1080/19427867.2021.1919469
- Da Costa, MB, Dos Santos, LMAL and Schaefer, JL. 2019. Industry 4.0 technologies basic network identification. Scientometrics, 121(2): 977–994. DOI: 10.1007/s11192-019-03216-7
- Gupta, MK and Chandra, PA. 2020. Comprehensive survey of data mining. International Journal of Information Technology, 12(4): 1243–1257. DOI: 10.1007/s41870-020-00427-7
- He, Q. 2021. Research on promoting the employment of college graduates with ideological and political education in the New Situation. Advances in Educational Technology and Psychology, 5(3): 141–145. DOI: 10.23977/aetp.2021.53020
- Hossain, MZ, et al. 2019. A dynamic K-means clustering for data mining. Indonesian Journal of Electrical Engineering and Computer Science, 13(2): 521–526. DOI: 10.11591/ijeecs.v13.i2.pp521-526
- Jeong, YJ, Lee, J, Moon, J, Shin, JH and Lu, WD. 2018. K-means data clustering with memristor networks. Nano letters, 18(7): 4447–4453. DOI: 10.1021/acs.nanolett.8b01526
- Lakshmi, K, Visalakshi, NK and Shanthi, S. 2018. Data clustering using k-means based on crow search algorithm. Sādhanā, 43(11): 1–12. DOI: 10.1007/s12046-018-0962-3
- Laxmi Lydia, E, et al. 2020. Charismatic document clustering through novel K-Means non-negative matrix factorization (KNMF) algorithm using key phrase extraction. International Journal of Parallel Programming, 48(3): 496–514. DOI: 10.1007/s10766-018-0591-9
- Liu, L, et al. 2021. An improved approach for mining association rules in parallel using Spark Streaming. International Journal of Circuit Theory and Applications, 49(4): 1028–1039. DOI: 10.1002/cta.2935
- Neysiani, BS, et al. 2019. Improve performance of association rule-based collaborative filtering recommendation systems using genetic algorithm. International Journal of Information Technology and Computer Science, 11(2): 48–55. DOI: 10.5815/ijitcs.2019.02.06
- Safara, F, Souri, A and Serrizadeh, M. 2020. Improved intrusion detection method for communication networks using association rule mining and artificial neural networks. IET Communications, 14(7): 1192–1197. DOI: 10.1049/iet-com.2019.0502
- Salal, YK, Abdullaev, SM and Kumar, M. 2019. Educational data mining: Student performance prediction in academic. International Journal of Engineering and Advanced Tech, 8(4C): 54–59.
- Shrifan, NHMM, Akbar, MF and Isa, NAM. 2022. An adaptive outlier removal aided k-means clustering algorithm. Journal of King Saud University-Computer and Information Sciences, 34(8): 6365–6376. DOI: 10.1016/j.jksuci.2021.07.003
- Subha, RP. 2019. Tree oriented association rule mining of multiple data sources. International Journal of Enterprise Network Management, 10(3–4): 272–279. DOI: 10.1504/IJENM.2019.103156
- Sun, H. 2019. Study on application of data mining technology in university computer network educational administration management system. Journal of Intelligent & Fuzzy Systems, 37(3): 3311–3318. DOI: 10.3233/JIFS-179133
- Thottathyl, H, Kanadam, KP and Panchadula, RP. 2020. Microarray breast cancer data clustering using map reduce based K-Means algorithm. Rev. d’Intelligence Artif, 34(6): 763–769. DOI: 10.18280/ria.340610
- Trakunphutthirak, R and Lee, VCS. 2022. Application of educational data mining approach for student academic performance prediction using progressive temporal data. Journal of Educational Computing Research, 60(3): 742–776. DOI: 10.1177/07356331211048777
- Wang, C and Zheng, X. 2020. Application of improved time series Apriori algorithm by frequent itemsets in association rule data mining based on temporal constraint. Evolutionary Intelligence, 13(1): 39–49. DOI: 10.1007/s12065-019-00234-5
- Wang, L and Soo-Jin, C. 2021. Sustainable development of college and university education by use of data mining methods. International Journal of Emerging Technologies in Learning (Online), 16(5): 102. DOI: 10.3991/ijet.v16i05.20303
- Xia, Y. 2021. Big data based research on the management system framework of ideological and political education in colleges and universities. Journal of Intelligent & Fuzzy Systems, 40(2): 3777–3786. DOI: 10.3233/JIFS-189411
- Zhan, Y, Tan, KH and Huo, B. 2019. Bridging customer knowledge to innovative product development: a data mining approach. International Journal of Production Research, 57(20): 6335–6350. DOI: 10.1080/00207543.2019.1566662