Dynamic constraint mining of frequent neighboring class sets
Gang Fang · Computer Engineering and Applications Journal · 2012
In frequent neighboring class sets mining,for the dynamic change of constraint condition given by user,present mining algorithms have redundant computing since they over and over scan spatial transactions.Hence,this paper proposes a dynamic constraint mining algorithm of frequent neighboring class sets,which can extract frequent neighboring class sets meeting user demand according to dynamic constraint instruction given by user.The algorithm uses array index to map neighboring class sets,and uses positive integer power set method to compute support and search frequent neighboring class sets meeting user's dynamic constraint.The algorithm needn't create candidate frequent neighboring class sets and repeat scanning spatial transaction from buffer analysis.In order to verify the algorithm is practical and effective,it is applied to mobile environment to shorten response time of mobile system to try their best to improve client satisfaction.In mobile computing the simulate experiment indicates that the algorithm is faster and more efficient than present algorithm.