Abstract: The support vector machine (SVM) and mean cluster data mining algorithm,almost all rely on the correlation between data,complete data matching．Once the database contains a large amount of redundancy data,the correlation between data will be reduced,and relevance is destroyed,resulting in traditional data mining algorithm efficiency lower．In order to avoid the above defects,this paper proposed a weakening association rules repair mining algorithm．In the data selection process,the method will not make initial classification processing for all elements only calculates proba-bility that one element belongs to a category,and determines multiple weak clustering center,calculates weak clustering relevance between different data,so as to realize the association rules weaker redundancy environment accurate data mining．The experimental results show that this algorithm can effectively improve the massive redundant environment data mining efficiency,has made the satisfactory effect.

Key words: Mass redundancy,Data mining,Association rules