基于改进Apriori算法的高校体测数据关联分析  

Association Analysis of College Physical Fitness Test Data Based on Improved Apriori Algorithm

作　　者：蒋茜茜 杨风暴[1] 杨童瑶 张锦荣 JIANG Xi-Xi;YANG Feng-Bao;YANG Tong-Yao;ZHANG Jin-Rong(School of Information and Communication Engineering,North University of China,Taiyuan 030051,China)

机构地区：[1]中北大学信息与通信工程学院,太原030051

出　　处：《计算机系统应用》2022年第5期345-350,共6页Computer Systems & Applications

摘　　要：为了能有效地分析高校体能测试数据且快速地反馈影响学生体测成绩的因素,本文以我校体能测试数据为样本,先进行数据预处理转换成适用于数据挖掘的数据集,考虑到体测数据特征有限并且长度一致的特点,采用事务压缩技术与hash技术相结合的Apriori算法进行数据分析,减少了遍历数据库的次数和生成的候选项集的规模,在保证挖掘精度的同时提高算法的运行效率.最后与Apriori算法、基于事务压缩的Apriori算法、基于hash技术的Apriori算法进行对比分析,实验结果表明,本文提出的事务压缩和hash技术相结合的改进Apriori算法,能有效地分析出学生体测成绩间的关联规则,对学生的体能训练具有更强的指导意义,与Apriori算法相比,运行效率提高了85%以上.To effectively analyze college physical fitness test data and quickly feed back the factors that affect students’ test results, this study takes the physical fitness test data of the North University of China as the sample and transforms preprocessed data into datasets suitable for data mining. Considering the limited features and consistent length of physical fitness test data, an Apriori algorithm that combines the transaction reduction technique with the hash technique is used to analyze data, which reduces the number of database traversal and the scale of candidate sets generated. It also improves the efficiency of the algorithm and ensures mining accuracy at the same time. Finally, comparison and analysis are made with the Apriori algorithm, the Apriori algorithm based on transaction reduction, and the Apriori algorithm based on the hash technique. The experimental results show that the proposed improved Apriori algorithm that combines transaction reduction and the hash technique can effectively analyze the association rules among students’ physical fitness test results and therefore has a stronger guiding significance for students’ physical fitness training. Compared with the Apriori algorithm, the proposed algorithm improves the operation efficiency by more than 85%.

关 键 词：事务压缩 HASH APRIORI 关联规则 

分 类 号：G804.49[文化科学—运动人体科学] G807.4[文化科学—体育学] TP311.13[自动化与计算机技术—计算机软件与理论]