CAJ | 학술논문

Apriori算法是关联规则挖掘的一个经典算法,针对Apriori算法的不足,提出了基于邻接矩阵的算法,该算法首先用邻接矩阵将事务数据库表示出来,然后基于邻接矩阵生成频繁k-项集。以高校图书馆借阅历史数据的挖掘为例,详细描述了事务数据库相应的邻接矩阵生成算法、k-项集生成算法以及相应的数据结构设计,算法均采用C语言描述。
Apriori산법시관련규칙알굴적일개경전산법,침대Apriori산법적불족,제출료기우린접구진적산법,해산법수선용린접구진장사무수거고표시출래,연후기우린접구진생성빈번k-항집。이고교도서관차열역사수거적알굴위례,상세묘술료사무수거고상응적린접구진생성산법、k-항집생성산법이급상응적수거결구설계,산법균채용C어언묘술。
The Apriori algorithm is a classical method of association rule mining,to the deficiency of Apriori algorithm,an improved Apriori algorithm based on the adjacent matrix was put forward.This algorithm converted the affair database to adjacent matrix and operated it to find out k-frequent item sets.As an instance,the lending data of university library＇s data mining of this improved algorithm was explored,which included data structure and the improved algorithm were scribed by using C programming language in detail.