计算机工程与科学2012，Vol.34Issue(9)：174-179,6.DOI:10.3969/j.issn.1007-130X.2012.09.031
改进的多维关联规则算法研究及应用
Research and Application of Improved Multidimensional Association Rule Mining Algorithms
摘要
Abstract
The field of data mining association rules is one of the most important and active areas . Taking the Apriori algorithm as a premise , using the Affairs compression idea of AprioriTid algorithms, we reduce the duplication of time scanning the database. We put forward a kind of Apriori algorithm based on the identifier lists of transactions in the database, and the list length is the candidate sets' corresponding support count. For getting the support count in the calculation, we only need to count the length of the list, thereby reducing the calculation time. At the same time, introducing the address indexing mechanism when generating frequent itemsets in the pruning process, we use the first set of candidate elements in the address table index to quickly locate, and thus reduce the number of scanning the transaction database. We make use of the business address index table to improve the counting time and execution efficiency of algorithms. The data of scientific research management as the research object, we use the improved algorithms to analyze the data of relationship, moreover, to extract the data's hidden , valuable information, and support the next phase of scientific research management. The experiments show that the algorithm is more efficient.关键词
关联规则/数据挖掘/Apriori算法/地址索引Key words
association rule/data mining/apriori algorithm/allocation index分类
信息技术与安全科学引用本文复制引用
张素琪,梁志刚,胡利娟,董永峰..改进的多维关联规则算法研究及应用[J].计算机工程与科学,2012,34(9):174-179,6.基金项目
天津市自然科学基金资助项目(10JCZDJC16000) （10JCZDJC16000）
