期刊文献+

关联规则在医药云数据定向中的应用与仿真 被引量:3

Application and Simulation of Association Rules in Medicine Cloud Data Orientation
下载PDF
导出
摘要 研究医药云数据的高效定向提取问题,提高数据提取的准确性和效率。受医药云数据复杂特性的限制使得从云数据中定向提取有效的信息较困难,当医药数据描述比较模糊时医药数据特征不明显,传统的云数据定向提取Apriori方法不能准确完成提取,提取过程需多次扫描数据库造成医药云数据定向提取的效率低、准确度不高。为解决上述难题,提出了关联规则应用在医药云数据定向提取中。引入模糊集理论和语义关联规则概念对描述模糊的医药数据提取请求进行合理转换解释,解决描述模糊的云数据准确提取,然后通过调整扫描项集的大小避免多次扫描数据库,以达到提高数据提取效率的目的。仿真结果表明,上述方法能够完成医药云数据的高效定向提取,保证提取的准确度和效率。 Efficient directional extraction problem of pharmaceutical cloud data was studied to improve the accuracy and efficiency of the data extraction. The association rules was used in the pharmaceutical cloud data oriented extraction. Fuzzy set theory and the concept of semantic association rules were introduced to reasonablely transform and explain the pharmaceutical data extraction requests which were described vaguely, and the cloud data were accurately extracted achieved. Then by adjusting the size of the scan set, multiple scans of database were avoided to improve data extraction efficiency. Simulation results show that the completion of the above method can realize the efficient orientation of pharmaceutical cloud data extraction and ensure the accuracy and efficiency of extractions.
出处 《计算机仿真》 CSCD 北大核心 2013年第2期239-242,共4页 Computer Simulation
关键词 关联规则 云数据 定向提取 Association rules Cloud data Directional extraction
  • 相关文献

参考文献6

二级参考文献64

  • 1王俊峰,杨建华,周虹霞,谢高岗,周明天.网络测量中自适应数据采集方法(英文)[J].软件学报,2004,15(8):1227-1236. 被引量:11
  • 2魏红宁.基于SPRINT方法的并行决策树分类研究[J].计算机应用,2005,25(1):39-41. 被引量:18
  • 3Sims K. IBM introduces ready-to-use cloud computing collaboration services get clients started with cloud computing. 2007. http://www-03.ibm.com/press/us/en/pressrelease/22613.wss 被引量:1
  • 4Boss G, Malladi P, Quan D, Legregni L, Hall H. Cloud computing. IBM White Paper, 2007. http://download.boulder.ibm.com/ ibmdl/pub/software/dw/wes/hipods/Cloud_computing_wp_final_8Oct.pdf 被引量:1
  • 5Zhang YX, Zhou YZ. 4VP+: A novel meta OS approach for streaming programs in ubiquitous computing. In: Proc. of IEEE the 21st Int'l Conf. on Advanced Information Networking and Applications (AINA 2007). Los Alamitos: IEEE Computer Society, 2007. 394-403. 被引量:1
  • 6Zhang YX, Zhou YZ. Transparent Computing: A new paradigm for pervasive computing. In: Ma JH, Jin H, Yang LT, Tsai JJP, eds. Proc. of the 3rd Int'l Conf. on Ubiquitous Intelligence and Computing (UIC 2006). Berlin, Heidelberg: Springer-Verlag, 2006. 1-11. 被引量:1
  • 7Barroso LA, Dean J, Holzle U. Web search for a planet: The Google cluster architecture. IEEE Micro, 2003,23(2):22-28. 被引量:1
  • 8Brin S, Page L. The anatomy of a large-scale hypertextual Web search engine. Computer Networks, 1998,30(1-7): 107-117. 被引量:1
  • 9Ghemawat S, Gobioff H, Leung ST. The Google file system. In: Proc. of the 19th ACM Symp. on Operating Systems Principles. New York: ACM Press, 2003.29-43. 被引量:1
  • 10Dean J, Ghemawat S. MapReduce: Simplified data processing on large clusters. In: Proc. of the 6th Symp. on Operating System Design and Implementation. Berkeley: USENIX Association, 2004. 137-150. 被引量:1

共引文献1348

同被引文献44

  • 1尤建良.胆囊癌中医治疗心得[J].陕西中医,2008,29(6):762-763. 被引量:7
  • 2胡慧蓉,王周敬.一种基于关系矩阵的关联规则快速挖掘算法[J].计算机应用,2005,25(7):1577-1579. 被引量:21
  • 3尤建良.晚期胆囊癌论治先肝后脾[J].四川中医,2007,25(9):51-52. 被引量:5
  • 4刁宇.基于属性矩阵的关联规则挖掘算法研究[C]∥2005年贵州制约逻辑学会学术年会暨首届全国性逻辑系统专题研讨会论文集.2005. 被引量:1
  • 5AGRAWAL R, IMIELINSKI T, SWAMI A. Mining association rules between sets of items in large databases [ J ]. ACM SIGMOD Record, 1993,22 (2) : 207 - 216. 被引量:1
  • 6JIAN P, XIAOLING W. An improved association rule algo- rithm based on Itemset Matrix and Cluster Matrix [ C ] // IEEE 7th International Conference on Computer Science & Education( ICCSE). 2012:834 - 837. 被引量:1
  • 7SUN S, ZAMBRENO J. Mining association rules with sys- tolic trees [ C ] //IEEE International Conference on Field Programmable Logic and Applications. 2008 : 143 - 148. 被引量:1
  • 8NOMA N G, GHANI A, KHANAPI M. Discovering pattern in medical audiology data with FP-growth algorithm [ C ]// IEEE EMBS Conference on Biomedical Engineering and Sciences( IECBES). 2012 : 17 - 22. 被引量:1
  • 9CHEUNG D W, HAN J, NG V T, et al. Maintenance of discovered association rules in large databases:An incre- mental updating technique [ C ]//IEEE Proceedings of the 12th International Conference on Data Engineering. 1996: 106 - 114. 被引量:1
  • 10Jiawei Han, Micheline Kanber. Data Mining: Concepls and Techniques. USA Morgan Kaufmann Publishers Jnc, 200 I, 7:5-11. 被引量:1

引证文献3

二级引证文献14

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部