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Reference
[1] Chen, M.S., Han, J., and Yu, P.S. (1996), “Data mining: An overview from a databaseperspective,”IEEE Transactions on Knowledge and Data Engineering, 8(6), 866-883.
[2] Han, J. and Kamber, M. (2001), Data Mining: Concepts and Techniques, New York: Academic Press.
[3] Cai, Y., Cercone, N., and Han, J. (1990), “An attribute-oriented approach for learning classification rules from relational databases,” in Proceedings of Sixth International Conference on Data Engineering, 281–288.
[4] Han, J., Cai, Y., and Cercone, N. (1992), “Knowledge discovery in databases: An attribute-oriented approach,” in Proceedings of International Conference on Very Large Data Bases, 547-59.
[5] Han, J., Cai, Y., and Cercone, N. (1993), “Data-driven discovery of quantitative rules in relational databases,”IEEE Transactions on Knowledge and Data Engineering, 5(1), 29-40.
[6] Han, J., Cai, Y., and Cercone, N. (1993), “Data-driven discovery of quantitative rules in relational databases,”IEEE Transactions on Knowledge and Data Engineering, 5(1), 29-40.
[7] Lu, W., Han, J., Ooi, B.C., (1993), “Discovery of general knowledge in large spatial databases,” In: Proceedings of 1993 Far East Workshop on Geographic Information Systems (FEGIS-93), 275-289.
[8] Carter, C.L. and Hamilton, H.J. (1995), “Performance evaluation of attribute-oriented algorithms for knowledge discovery from databases,” in Proceedings of Seventh International Conference on Tools with Artificial Intelligence, 486–489.
[9] Carter, C.L. and Hamilton, H.J. (1998), “Efficient attribute-oriented generalization for knowledge discovery from large databases,”IEEE Transactions on Knowledge and Data Engineering, 10(2), 193-208.
[10] Cheung, D.W., Hwang, H.Y., Fu, A.W., and Han, J. (2000), “Efficient rule-based attribute-oriented induction for data mining,”Journal of Intelligent Information Systems, 15(2), 175-200.
[11] Hamilton, H.J., Hilderman, R.J., and Cercone, N. (1996), “Attribute-oriented induction using domain generalization graphs,” in Proceedings of Eighth IEEE International Conference on Tools with Artificial Intelligence, 246-52.
[12] McClean, S., Scotney, B., Shapcott, M., (2000), “Incorporating domain knowledge into attribute-oriented data mining,” International Journal of Intelligent Systems, 15 (6), 535-548.
[13] Hamilton, H.J., Hilderman, R.J., and Cercone, N. (1996), “Attribute-oriented induction using domain generalization graphs,” in Proceedings of Eighth IEEE International Conference on Tools with Artificial Intelligence, 246-52.
[14] S. Tsumoto(2000), “Knowledge discovery in clinical databases and evaluation of discovered knowledge in outpatient clinic”, Information Sciences 124(1) 125-37.
[15] Y. L. Chen, C. C. Shen, (2005), “Mining generalized knowledge from ordered data through attribute-oriented induction techniques,”European Journal of Operational Research, 166, 221–245.
[16] C.L. Carter and H.J. Hamilton(1998), “Efficient attribute-oriented generalization for knowledge discovery from large databases,” IEEE Transactions on Knowledge and Data Engineering, 10(2) 193-208.
[17] C.-C. Hsu(2004), “Extending attribute-oriented induction algorithm for major values and numeric values,” Expert Systems with Applications , 27(2) 187-202.
[18] K.M. Lee(2001), “Mining generalized fuzzy quantitative association rules with fuzzygeneralization hierarchies,” Joint 9th IFSA World Congress and 20th NAFIPS International Conference, 2977-82.
[19] G. Raschia and N. Mouaddib, Saintetiq, (2002): A fuzzy set-based approach to database summarization, Fuzzy Sets and Systems, 129(2) 137-62.
[20] R.A. Angryk and F.E. Petry, (2005),“Mining multi-level associations with fuzzy hierarchies,” The 14th IEEE International Conference on Fuzzy Systems, FUZZ''05. 785-90.
[21] U. Hierarchies, (1997), “Database summarization using fuzzy isa hierarchies,”IEEE Transactions on Systems, Man, and Cybernetics-Part B, 27(1) 68-78.
[22] E.M. Knorr and R.T. Ng, (1996), “Extraction of spatial proximity patterns by concept generalization,” Second International Conference on Knowledge Discovery and Data Mining, 347–50.
[23] L.Z. Wang, L.H. Zhou and T. Chen, (2004),“A new method of attribute-oriented spatial generalization,”Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 1393-8.
[24] S. Tsumoto, (2000),“Knowledge discovery in clinical databases and evaluation of discovered knowledge in outpatient clinic,”Information Sciences, 124(1) 125-37.
[25] Chen, Y.-L., Hsu, C.-L., and Chou, S.-C. (2003),“Constructing a Multi-valued and Multi-labeled Decision Tree,”Expert Systems with Applications, 25(2), 199-209.
[26] Jun-Rong Huang. (2006), “Using clusters to find the most adaptive recommendations of books” Journal of Educational Media & Library Science, 43(3), 309-325.
[27] Ou, J., Lin, S. and Li, J. (2001), “The Personalized Index Service System in Digital Library,” Proc. of the Third International Symposium on Cooperative Database Systems for Advanced Applications, 92-99.
[28] Schafer, J. B., Konstan,J. A. and Riedl,J. (2001), “ E-Commerce Recommendation Applications,” Data Mining and Knowledge Discovery, 5(1), 115-153.
[29] Ansari,A., Essengaier,S. and R. Kohli. (2000), “ Internet Recommendation Systems,” Journal of Marketing Research, 37(3), 363-375.
[30] Shu-Meng Huang. (2010), “ A study on the Modified Attributed-Oriented-Induction Algorithm of Mining the Multi-Value Attribute Data”, ICERM, 62.
[31]Lee,W.P., Liu,C.H. and Lu,C.C. (2002), “Intelligent agent- based systems for personalized recommendations in Internet commerce,” Expert Systems with Applications, 22(4), 275-284.
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