Research on Personality Mining System in E-Learning by Using Improved Association Rules

  • Authors:

  • Luo Qi;Yanwen Wu;Liyong Wan;Ying Yu

  • Affiliations:

  • Dept. of Info. & Technol., Central China Normal Univ., Wuhan, Hubei 430079, PRC, ccnu_luo2008@yahoo.com.cn, wyw_2002cn@yahoo.com.cn and Dept. of Info. Eng., Wuhan Univ. of Sci. and Technol., Zhong ...;Department of Information & Technology, Central China Normal University, Wuhan, Hubei 430079, P.R.China, ccnu_luo2008@yahoo.com.cn, wyw_2002cn@yahoo.com.cn;Department of Information & Technology, Central China Normal University, Wuhan, Hubei 430079, P.R.China, ccnu_luo2008@yahoo.com.cn, wyw_2002cn@yahoo.com.cn;Department of Information & Technology, Central China Normal University, Wuhan, Hubei 430079, P.R.China, ccnu_luo2008@yahoo.com.cn, wyw_2002cn@yahoo.com.cn

  • Venue:
  • Proceedings of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding
  • Year:
  • 2006

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Abstract

To meet the personalized needs of E-learning, an improved association mining rules was proposed in the paper. First, data cube from database was established. Then, frequent item-set that satisfies the minimum support on data cube was mined out. Furthermore, association rules of frequent item-set were generated. Finally, redundant association rules through the relative method in statistics were wiped off. The algorithm had two advantages, the first was that the execution time was short while searching for the frequent item-set; the second was that the precision of the rules was high. The algorithm was also used in personality mining system based on E-learning model (PMSEM).The results manifested that the algorithm was effective.