CAJ | 학술논문

物联网数据挖掘处理的是海量数据，当前数据挖掘的一个研究热点就是在大规模数据集中快速有效地提取用户所需的信息。对传统Apriori算法做相应的改进，使得检索出全部的频繁项集，只要对事务数据库进行一遍扫描就可以完成，将该Apriori算法进行Map/Reduce化，利用云计算的分布式并行计算的性质，将其应用到基于云计算的物联网数据挖掘，实验验证了改进的Apriori算法的有效性。
물련망수거알굴처리적시해량수거，당전수거알굴적일개연구열점취시재대규모수거집중쾌속유효지제취용호소수적신식。대전통Apriori산법주상응적개진，사득검색출전부적빈번항집，지요대사무수거고진행일편소묘취가이완성，장해Apriori산법진행Map/Reduce화，이용운계산적분포식병행계산적성질，장기응용도기우운계산적물련망수거알굴，실험험증료개진적Apriori산법적유효성。
The internet of things data mining usually need to process massive amounts of data .Recently, how to find useful in-formation has become the hotspot of data mining in massive data .In the present work, we improve the Apriori algorithm to scan the transaction database only, and to find all frequent itemsets.Furthermore, using cloud computing and distributed parallel computing nature, the Apriori algorithm is Mapped/Reduced, and is applied to the cloud computing and internet of things based on data min-ing.Through the experiment, we verify the effectiveness of the improved Apriori algorithm.