Personality Mining System in E-Learning by using Improved Association Rules

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 was 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 result manifested that the algorithm was effective.