计算机科学 ›› 2019, Vol. 46 ›› Issue (10): 71-76.doi: 10.11896/jsjkx.190100223
王斌, 马俊杰, 房新秀, 魏天佑
WANG Bin, MA Jun-jie, FANG Xin-xiu, WEI Tian-you
摘要： 基于时间戳的关联规则挖掘算法(SLMCM)主要用于解决新增项的问题,但效率较低,难以适应大数据挖掘。针对这个问题,文中提出了改进算法E-SLMCM和DE-SLMCM。E-SLMCM算法采用垂直结构,仅需遍历数据库两次,在将数据库转化为垂直格式时,可直接记录各项的时间戳,且不需要将每条事务的各项按时间戳进行排序;另外,提出了新的求项集时间戳的方法,在求更高项集的时间戳时不用多次遍历数据库。E-SLMCM算法适合应用于稀疏数据库,为了提高在密集数据库上的运行效率,在E-SLMCM算法的基础上采用差集思想提出了DE-SLMCM算法。所列举的4个基于公共数据集的仿真实验中,在不同最小支持度条件下,E-SLMCM和DE-SLMCM分别在稀疏和密集数据集上运行的时间效率是SLMCM的10~1 000倍。
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| [1]AGRAWAL R,IMIELIHSKI T,SWAMI A.Mining association rules between sets of items in large databases[J].Acm sigmod record,1993,22(2):207-216. [2]HAN J,PEI J,YIN Y .Mining Frequent Patterns Without Candidate Generation[C]//Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data.Dallas,Te-xas,USA:ACM,2000. [3]ZAKI M J.Scalable algorithms for association mining[J].IEEE transactions on knowledge and data engineering,2000,12(3):372-390. [4]RASHID M M,GONDAL I,KAMRUZZAMAN J.Mining associated patterns from wireless sensor networks[J].IEEE Tran-sactions on Computers,2015,64(7):1998-2011. [5]WANG L,MENG J,XU P,et al.Mining temporal association rules with frequent itemsets tree[J].Applied Soft Computing,2018,62:817-829. [6]CHEN C H,LAN G C,HONG T P,et al.Mining fuzzy temporal association rules by item lifespans[J].Applied Soft Computing,2016,41:265-274. [7]ZOU C,DENG H,WAN J,et al.Mining and updating association rules based on fuzzy concept lattice[J].Future Generation Computer Systems,2018,82:698-706. [8]MIHOLCA D L,CZIBULA G,CRIVEI L M.A new incremental relational association rules mining approach[J].Procedia Computer Science,2018,126:126-135. [9]NGUYEN D,LUO W,PHUNG D,et al.LTARM:A novel temporal association rule mining method to understand toxicities in a routine cancer treatment[J].Knowledge-Based Systems,2018,161:313-328. [10]ZHANG S C,ZHANG J L,CHEN F,et al.Negative Incremental Updating Algorithm for Maintaining Association rules[J].Computer Science,2005,32(9):153-155.(in Chinese) 张师超,张继连,陈峰,等.负增量式关联规则更新算法[J].计算机科学,2005,32(9):153-155. [11]CAI J,XUE Y S,LIN L,et al.Updating Algorithm for Association Rules Based on Fully M ining Incremental Transactions[J].Computer Science,2007,34(2):220-222.(in Chinese) 蔡进,薛永生,林丽,等.基于充分挖掘增量事务的关联规则更新算法[J].计算机科学,2007,34(2):220-222. [12]GAN W,LIN C W,FOURNIER-VIGER P,et al.Mining of frequent patterns with multiple minimum supports[J].Engineering Applications of Artificial Intelligence,2017,60(C):83-96. [13]DARRAB S,ERGENC B.Vertical Pattern Mining Algorithm for Multiple Support Thresholds[J].Procedia ComputerScien-ce,2017,112:417-426. [14]HU H W,CHANG H C,LIN W S,et al.An optimized frequent pattern mining algorithm with multiple minimum supports[C]//IEEE International Conference on Big Data.IEEE,2017. [15]DAHBI A,BALOUKI Y,GADI T.Using Multiple Minimum Support to Auto-adjust the Threshold of Support in Apriori Algorithm[C]//International Conference on Soft Computing and Pattern Recognition.Cham:Springer,2017:111-119. [16]WENG C H.Identifying association rules of specific later-marketed products[J].Applied Soft Computing,2016,38:518-529. [17]GAO J,SHI B L.Research on Fast Association Rule Mining Algorithm[J].Computer Science,2005,32(3):200-201.(in Chinese) c高俊,施伯乐.快速关联规则挖掘算法研究[J].计算机科学,2005,32(3):200-201. [18]LIU D,LIU Y,YIN Z.Fast algorithm for discovering maximum frequent itemsets of association rules[J].Acta Scientiarium Natu-ralium Universitatis Jilinensis,2004,42(2):212-215. [19]ZAKI M J,GOUDA K.Fast vertical mining using diffsets[C]//Proceedings of the Ninth ACM SIGKDD International Confe-rence on Knowledge Discovery and Data Mining.ACM,2003:326-335. [20]FOURNIER-VIGER P,GOMARIZ A,SOLTANI A,et al. SPMF:OpenSource Data Mining Platform[EB/OL].http://www.philippe-fournier-viger.com/spmf. |
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