CAJ | 학술논문

在当今这个信息极度发达的社会，网络数据急剧膨胀，激增的数据背后隐藏着许多重要的信息，所以对大量数据进行分析是必要的。Apriori算法是一种挖掘关联规则的频繁项集算法，其核心思想是通过候选集生成和情节的向下封闭检测两个阶段来挖掘频繁项集。可能产生大量的候选集，以及可能需要重复扫描数据库是Apriori算法的两大缺点。文中提出了一种需要更少的扫描时间的Apriori算法，在剪枝候选项集的同时也在消除冗余的子项集的产生。改进的Apriori算法通过消除数据库中不需要记录的传输有效减少了I/O所花费的时间，Apriori算法的效率得到了极大的优化。文章给出了算法实现思想及证明，并对传统的和改进的Apriori算法进行比较和分析。
재당금저개신식겁도발체적사회，망락수거급극팽창，격증적수거배후은장착허다중요적신식，소이대대량수거진행분석시필요적。Apriori산법시일충알굴관련규칙적빈번항집산법，기핵심사상시통과후선집생성화정절적향하봉폐검측량개계단래알굴빈번항집。가능산생대량적후선집，이급가능수요중복소묘수거고시Apriori산법적량대결점。문중제출료일충수요경소적소묘시간적Apriori산법，재전지후선항집적동시야재소제용여적자항집적산생。개진적Apriori산법통과소제수거고중불수요기록적전수유효감소료I/O소화비적시간，Apriori산법적효솔득도료겁대적우화。문장급출료산법실현사상급증명，병대전통적화개진적Apriori산법진행비교화분석。
In the highly developed information society, network data expand rapidly and much important information hide behind the surge of data. So it is necessary that analyze a large amounts of data. Apriori algorithm is a frequent item set algorithm for mining association rules. Its core idea is to excavate frequent item sets through two stages including generating candidate sets and closed down testing of plot. May generate a large number of candidate sets and may need to repeat scanning database are the two major drawbacks of Apriori algorithm. By eliminating unnecessary transmission of records in the database, the improved Apriori algorithm effectively reduces the time spent on I/O, greatly optimizes the efifciency of the algorithm, proves and gives the algorithm implementation thought. In this paper, an enhanced Apriori algorithm is proposed which takes less scanning time. It is achieved by eliminating the redundant generation of sub-items during pruning the candidate item sets. Both traditional and enhanced Apriori algorithms are compared and analyzed in this paper.