Application of an Improved Sequence Pattern Association Rule Algorithm-based Data Management System for Continuing Education Teaching Data in Universities
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Agrawal, R., & Srikant, R. (1995). Mining sequential patterns. Proceedings of the 11th International Conference on Data Engineering, 3-14.AgrawalR.SrikantR. (1995). Mining sequential patterns. Proceedings of the 11th International Conference on Data Engineering, 3-14.Search in Google Scholar
Fayyad, U. M., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI Magazine, 17(3), 37-54.FayyadU. M.Piatetsky-ShapiroG.SmythP. (1996). From data mining to knowledge discovery in databases. AI Magazine, 17(3), 37-54.Search in Google Scholar
Srikant, R., & Agrawal, R. (1996). Mining sequential patterns: Generalizations and performance improvements. Proceedings of the 5th International Conference on Extending Database Technology, 317.SrikantR.AgrawalR. (1996). Mining sequential patterns: Generalizations and performance improvements. Proceedings of the 5th International Conference on Extending Database Technology, 317.Search in Google Scholar
Agrawal, R., & Srikant, R. (1995). Fast algorithms for mining association rules. Proceedings of the 21th International Conference on Very Large Data Bases (VLDB), 487–499.AgrawalR.SrikantR. (1995). Fast algorithms for mining association rules. Proceedings of the 21th International Conference on Very Large Data Bases (VLDB), 487–499.Search in Google Scholar
Srikant, R., & Agrawal, R. (1996). Mining quantitative association rules in large relational tables. Proceedings of the ACM SIGMOD International Conference on Management of Data, 1–12.SrikantR.AgrawalR. (1996). Mining quantitative association rules in large relational tables. Proceedings of the ACM SIGMOD International Conference on Management of Data, 1–12.Search in Google Scholar
Chen, W., & Zhang, H. (2010). Mining sequential patterns using a hybrid model. Data Mining and Knowledge Discovery, 20(2), 266-284.ChenW.ZhangH. (2010). Mining sequential patterns using a hybrid model. Data Mining and Knowledge Discovery, 20(2), 266-284.Search in Google Scholar
Wei, X., & Zhang, W. (2015). A study of association rule mining and its application in education data analysis. Proceedings of the International Conference on Computational Intelligence and Software Engineering, 1-4.WeiX.ZhangW. (2015). A study of association rule mining and its application in education data analysis. Proceedings of the International Conference on Computational Intelligence and Software Engineering, 1-4.Search in Google Scholar
Zhang, Y., & Xu, B. (2018). Research on the application of association rule mining in education data management. Proceedings of the 4th International Conference on Education and Management Engineering, 105-111.ZhangY.XuB. (2018). Research on the application of association rule mining in education data management. Proceedings of the 4th International Conference on Education and Management Engineering, 105-111.Search in Google Scholar
Han, J., & Kamber, M. (2006). Data mining: Concepts and techniques (2nd ed.). Morgan Kaufmann.HanJ.KamberM. (2006). Data mining: Concepts and techniques (2nd ed.). Morgan Kaufmann.Search in Google Scholar
Hai, B., Zongkai, L., & Yuchai, G. (2000). FP-growth: Frequent itemset mining using data compression. Proceedings of the International Conference on Data Mining, 23-35.HaiB.ZongkaiL.YuchaiG. (2000). FP-growth: Frequent itemset mining using data compression. Proceedings of the International Conference on Data Mining, 23-35.Search in Google Scholar
Yao, X., Jiang, J., & Li, L. (2003). High utility itemset mining. Proceedings of the 2003 IEEE International Conference on Data Mining, 290-298.YaoX.JiangJ.LiL. (2003). High utility itemset mining. Proceedings of the 2003 IEEE International Conference on Data Mining, 290-298.Search in Google Scholar
Tseng, V. S., & Tseng, M. S. (2006). UP-Growth: A new algorithm for mining high-utility itemsets. Proceedings of the International Conference on Data Mining, 1056-1061.TsengV. S.TsengM. S. (2006). UP-Growth: A new algorithm for mining high-utility itemsets. Proceedings of the International Conference on Data Mining, 1056-1061.Search in Google Scholar
Wu, J., Zhang, M., & Li, Z. (2007). TKU algorithm for mining high utility itemsets. Proceedings of the 2007 International Conference on Data Mining, 179-186.WuJ.ZhangM.LiZ. (2007). TKU algorithm for mining high utility itemsets. Proceedings of the 2007 International Conference on Data Mining, 179-186.Search in Google Scholar
Li, H., Li, Z., & Liu, J. (2010). FHIMA: Frequent high utility itemset mining algorithm based on PrefixSpan. Proceedings of the International Conference on Knowledge Discovery and Data Mining, 287-293.LiH.LiZ.LiuJ. (2010). FHIMA: Frequent high utility itemset mining algorithm based on PrefixSpan. Proceedings of the International Conference on Knowledge Discovery and Data Mining, 287-293.Search in Google Scholar
Wu, Q., Li, Z., & Zhang, L. (2011). TKHUP: High utility pattern mining using projection. Proceedings of the International Conference on Data Science and Engineering, 45-56.WuQ.LiZ.ZhangL. (2011). TKHUP: High utility pattern mining using projection. Proceedings of the International Conference on Data Science and Engineering, 45-56.Search in Google Scholar
Pan, H., Zhang, Y., & Wang, Q. (2012). Domain knowledge-guided association rules for pattern mining of medical images. Journal of Medical Imaging and Health Informatics, 2(3), 123-129.PanH.ZhangY.WangQ. (2012). Domain knowledge-guided association rules for pattern mining of medical images. Journal of Medical Imaging and Health Informatics, 2(3), 123-129.Search in Google Scholar
Zhang, J., Liu, W., & Zhou, Y. (2014). DKARM: Domain knowledge guided algorithm for removing redundant itemsets. International Journal of Data Mining and Knowledge Discovery, 14(2), 189-200.ZhangJ.LiuW.ZhouY. (2014). DKARM: Domain knowledge guided algorithm for removing redundant itemsets. International Journal of Data Mining and Knowledge Discovery, 14(2), 189-200.Search in Google Scholar
Agrawal, R., & Srikant, R. (1993). Mining association rules between sets of items in large databases. Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, 207-216.AgrawalR.SrikantR. (1993). Mining association rules between sets of items in large databases. Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, 207-216.Search in Google Scholar
Shuai, H., Chuanzheng, L., & Katsuichiro, G. (2023). Applicability of smooth particle hydrodynamics method to large sliding deformation of saturated slopes under earthquake action. Chinese Journal of Geotechnical Engineering, 45(2), 336-344.ShuaiH.ChuanzhengL.KatsuichiroG. (2023). Applicability of smooth particle hydrodynamics method to large sliding deformation of saturated slopes under earthquake action. Chinese Journal of Geotechnical Engineering, 45(2), 336-344.Search in Google Scholar