并行拓展及关联分析的户外运动资源整合模型

Outdoor Sports Resource Integration Model Based on Parallel Expansion and Correlation Analysis

为了更好的对户外运动资源进行整合,以提高资源利用率,本文采用数据挖掘技术构建了一种并行拓展及关联分析的户外运动资源整合模型。首先将整个数据集随机分割成若干个非重叠子数据集,并且每个子数据集还可继续划分成更小的子集,进而并行分层地挖掘出局部频繁项集,然后根据频繁项集先验性质,连接局部频繁项集得到全局候选项集;最后扫描数据集统计出每个候选项集的实际支持度,以确定全局频繁项集。算法实例仿真结果表明,本文提出的改进算法与普通Apriori算法相比更高效,并且在户外运动资源整合的应用中,本文提出的算法表现出更好的挖掘效率。

In order to better integrate the outdoor sports resources to improve the resource utilization rate,this paper constructs an outdoor sports resource integration model with parallel expansion and correlationanalysis by using data mining technology.Firstly,the whole data set is randomly divided into severalnon-overlapping sub-datasets,and each sub-dataset can be divided into smaller subsets,and then thelocal frequent itemsets are excavated in parallel.Then,The final set of data items is counted to determinethe global frequent itemsets of each candidate set.The simulation results show that the improvedalgorithm proposed in this paper is more efficient than the conventional Apriori algorithm,and thealgorithm proposed in this paper shows better mining efficiency in the application of outdoor sportsresource integration.