CAJ | 학술논문

随着大数据时代的到来，如今人们已经淹没在海量的信息当中。云计算技术的出现，为解决在海量数据中高效地挖掘出有价值的信息问题提供了新的思路。利用云计算的分布式处理和虚拟化技术的优势，提出一种基于Map/Reduce编程模型与编码操作相结合的分布式关联规则挖掘算法———MCM-Apriori算法；设计并实现一个基于Hadoop云平台的网上图书销售系统。为进一步验证该系统的高效性，在该系统中利用MCM-Apriori算法进行图书推荐服务的应用。实验对比结果表明，该系统实现了快速分析与查询、可靠存储的功能，可以明显提高关联规则挖掘效率。
수착대수거시대적도래，여금인문이경엄몰재해량적신식당중。운계산기술적출현，위해결재해량수거중고효지알굴출유개치적신식문제제공료신적사로。이용운계산적분포식처리화허의화기술적우세，제출일충기우Map/Reduce편정모형여편마조작상결합적분포식관련규칙알굴산법———MCM-Apriori산법；설계병실현일개기우Hadoop운평태적망상도서소수계통。위진일보험증해계통적고효성，재해계통중이용MCM-Apriori산법진행도서추천복무적응용。실험대비결과표명，해계통실현료쾌속분석여사순、가고존저적공능，가이명현제고관련규칙알굴효솔。
With the advent of big data era, people are now overwhelmed by massive information.The emergence of cloud computing tech-nology provides new idea for efficiently mining the valuable information from mass data.By utilising its advantages in distributed processing and virtualisation, we present a distributed associate rule mining algorithm ( MCM-Apriori) , which is based on the combination of Map/Re-duce programming model and coding operation.We also design and implement an online bookstore sales system with Hadoop framework using cloud computing.To further verify the efficiency of the system, we use MCM-Apriori algorithm to implement the application of book recom-mendations service in it.Contrasted experimental results demonstrate that this system achieves the functions of fast analysis and query as well as reliable storage, and can significantly improve the efficiency of association rules mining.