1. 1. J. Han and M. Kamber, Data Mining: Concepts and Techniques, 2nd ed. SanFrancisco, CA, USA: Morgan Kaufmann, 2006.
   2. M.A.Hern´andez and S. J. Stolfo, ―Real-world data is dirty: Data cleansing and the merge/purge problem,‖ Data Mining Knowl. Discovery, vol. 2, no. 1, pp. 9–37, 1998K.
   3. M. Lenzerini, ―Data integration: A theoretical perspective,‖ in Proc. 21st ACMSIGMOD-SIGACTSIGART Symp. Principles Database Syst., Madison, WI, USA, 2002, pp. 233–246.
   4. A. S. C. Ehrenberg, Data Reduction: Analysing and Interpreting Statistical Data. New York, NY, USA: Wiley, 1975.
   5. M. Stacey and C. McGregor, ―Temporal abstraction in intelligent clinical data analysis: A survey,‖ Artif. Intell. Med., vol. 39, no. 1, pp. 1–24, 2007.
   6. Wei-Ti Su ,Xiao-Ou Ping, Yi-Ju Tseng, Feipei Lai,‖ Multiple Time Series Data Processing for Classification with Period Merging Algorithm‖, Procedia Computer Science 37 ( 2014 ) 301 – 308
   7. L. Breiman, ―Random forests,‖ Mach. Learning, vol. 45, no. 1, pp. 5–32,2001.
   8. Cortes and V. Vapnik, ―Support-vector networks,‖ Mach. Learning vol. 20, no. 3, pp. 273–297, 1995.
   9. Yi-Ju Tseng, Xiao-Ou Ping, Ja-Der Liang ―MultipleTime-Series Clinical Data Processing for Classification With Merging Algorithm and Statistical Measures‖ Ieee Journal Of Biomedical And Health Informatics, Vol. 19, No. 3, May 2015.
   10. Douglas Rodrigues, Luis A. M. Pereira, Jo’ao P. Papa,"A Binary Krill Herd Approach for Feature Selection",2014 22nd International Conference on Pattern Recognition.
   
   
2. 1. J. Han and M. Kamber, Data Mining: Concepts and Techniques, 2nd ed. SanFrancisco, CA, USA: Morgan Kaufmann, 2006
   2. M.A.Hern´andez and S. J. Stolfo, “Real-world data is dirty: Data cleansing and the merge/purge problem,” Data Mining Knowl. Discovery, vol. 2, no. 1, pp. 9–37, 1998K
   3. M. Lenzerini, “Data integration: A theoretical perspective,” in Proc. 21st ACMSIGMOD-SIGACTSIGART Symp. Principles Database Syst., Madison, WI, USA, 2002, pp. 233–246.
   4. A. S. C. Ehrenberg, Data Reduction: Analysing and Interpreting Statistical Data. New York, NY, USA: Wiley, 1975.
   5. M. Stacey and C. McGregor, “Temporal abstraction in intelligent clinical data analysis: A survey,” Artif. Intell. Med., vol. 39, no. 1, pp. 1–24, 2007.
   6. Wei-Ti Su ,Xiao-Ou Ping, Yi-Ju Tseng, Feipei Lai,” Multiple Time Series Data Processing for Classification with Period Merging Algorithm”, Procedia Computer Science 37 ( 2014 ) 301 – 308.
   7. L. Breiman, “Random forests,” Mach. Learning, vol. 45, no. 1, pp. 5–32,2001.
   8. Cortes and V. Vapnik, “Support-vector networks,” Mach. Learning vol. 20, no. 3, pp. 273–297, 1995
   9. Yi-Ju Tseng, Xiao-Ou Ping, Ja-Der Liang “MultipleTime-Series Clinical Data Processing for Classification With Merging Algorithm and Statistical Measures” Ieee Journal Of Biomedical And Health Informatics, Vol. 19, No. 3, May 2015.
   10. Douglas Rodrigues, Luis A. M. Pereira, Jo’ao P. Papa,"A Binary Krill Herd Approach for Feature Selection",2014 22nd International Conference on Pattern Recognition.