Please wait a minute...
New Technology of Library and Information Service  2007, Vol. 2 Issue (7): 59-62    DOI: 10.11925/infotech.1003-3513.2007.07.14
Current Issue | Archive | Adv Search |
Associate Data Mining Method Research Based on Grid System
Yang Mu1   Zhou Jiliu2   Hu Yanmei1
1(Center of Educational Technology, Chengdu Medical College,Chengdu 610083,China)
2(College of Computer Science, Sichuan University, Chengdu 610065,China)
Download:
Export: BibTeX | EndNote (RIS)      
Abstract  

This paper analyzes the requirements of data mining and introduces the common forms and existing problems in data mining. In the light of the problems,the authors discusse the associate data mining method of multimedia based on grid system which is the application of Apriori algorithm under the grid system. By analyzing the instance, the method is proved to have not only the accuracy of classics Apriori algorithm but also the characteristics of grid parallel excavation. Therefore, it can improve the data mining speed greatly and enhance the operation efficiency.

Key wordsMultimedia      Grid technology      Data mining      Apriori algorithm     
Received: 11 June 2007      Published: 25 July 2007
: 

TP393

 
Corresponding Authors: Yang Mu     E-mail: udjtrt@126.com
About author:: Yang Mu,Zhou Jiliu,Hu Yanmei

Cite this article:

Yang Mu,Zhou Jiliu,Hu Yanmei. Associate Data Mining Method Research Based on Grid System. New Technology of Library and Information Service, 2007, 2(7): 59-62.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2007.07.14     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2007/V2/I7/59

[1] HexM,ChuQX,ZhuMY.MiIIiIni Preemption Cost for Path Selection in DiffServ-ware MPLS Networks[J].Computer Communications,2006,29(18):3825-3832.
[2] Cho E H,Shin K S,Yoo S J.SIP-based QoS Support Architecture and Session Management in a Combined IntServ and DiffServ Networks[J].Computer Communications,2006,29(15):2996—3009.
[3] Ahmed N U, LU X,Barbosa L O. An Efficient Parallel Optimization Algorithm for the Token Bucket Control Mechanism [J].Computer Communications, 2006,29(12):2281-2293.
[4] Krauter K,Buyya R,Maheswaran  M.A Taxonomy and Survey of Grid Resource Management Systems for Distributed Computing[J].Software Practice and Experience.2002,32(2):135-164.
[5] Myllymaki J. Effective Web Data Extraction with Standard XML Technologies[C].In:Proceedings of the 10 International Conference on World Wide Web.New York:ACM Press,2001.
[6] Jiawei Han,Micheline Kamhr.Data Mining Concepts and Techniques[M].北京:机械工业出版社,2006.
[7] Zha L, Li W,Dafu D,et al.System Software for China National Grid[M].In:IFIP International Conference on Network and Parallel Computing 2005.Beijing, China,2005:14-21.
[8] Foster I,Kesselman C.网格计算[M].北京:电子工业出版社,2004:17-18.
[9] 王创新.关联规则提取中对Apriori算法的一种改进[J].计算机工程与应用,2004(34):183-185.
[10] 马盈仓.挖掘关联规则中Apriori算法的改进[J].计算机应用与软件,2004,21(11):82-84.
[11] 李清峰,杨路明,张晓峰,等.数据挖掘中关联规则的一种高效Ariori算法[J].计算机应用与软件,2004,21(12):84-86.
[12] 冯兴杰,周谆.Apriori算法的改进[J].计算机工程, 2005,31(B07):172-173.
[13] 刘君强,孙晓莹,潘云鹤.关联规则挖掘技术研究的新进展[J].计算机科学,2004,31(1):110-113.

[1] Xie Wang, Wang Lizhen, Chen Hongmei, Zeng Lanqing. Identifying Relationship Between Pollution Sources and Cancer Cases with Spatial Ordered Pair Patterns[J]. 数据分析与知识发现, 2021, 5(2): 14-31.
[2] Yong Zhang,Shuqing Li,Yongshang Cheng. Mining Algorithm for Weighted Association Rules Based on Frequency Effective Length[J]. 数据分析与知识发现, 2019, 3(7): 85-93.
[3] Quan Lu,Anqi Zhu,Jiyue Zhang,Jing Chen. Research on User Information Requirement in Chinese Network Health Community: Taking Tumor-forum Data of Qiuyi as an Example[J]. 数据分析与知识发现, 2019, 3(4): 22-32.
[4] Dongmei Mu,Hui Fa,Ping Wang,Jing Sun. Research on Disease Risk Factors on Structural Equation Model[J]. 数据分析与知识发现, 2019, 3(4): 80-89.
[5] Li Yongnan. Using Bayes Theory to Classify Counter Terrorism Intelligence[J]. 数据分析与知识发现, 2018, 2(10): 9-14.
[6] Mu Dongmei,Wang Ping,Zhao Danning. Reducing Data Dimension of Electronic Medical Records: An Empirical Study[J]. 数据分析与知识发现, 2018, 2(1): 88-98.
[7] Li Changbing,Pang Chongpeng,Li Meiping. Extracting Product Features with Weight-based Apriori Algorithm[J]. 数据分析与知识发现, 2017, 1(9): 83-89.
[8] Hu Zhongyi,Wang Chaoqun,Wu Jiang. Identifying Phishing Websites with Multiple Online Data Sources[J]. 数据分析与知识发现, 2017, 1(6): 47-55.
[9] Jiang Siwei,Xie Zhenping,Chen Meijie,Cai Ming. Self-Explainable Reduction Method for Mixed Feature Data Modeling[J]. 数据分析与知识发现, 2017, 1(12): 92-100.
[10] Mu Dongmei,Ren Ke. Discovering Knowledge from Electronic Medical Records with Three Data Mining Algorithms[J]. 现代图书情报技术, 2016, 32(6): 102-109.
[11] Li Feng,Li Shu’ning,Yu Jing. A Department Oriented Library Usage Data System for Graduates[J]. 现代图书情报技术, 2016, 32(5): 99-103.
[12] Dun Wenjie, Sun Yigang, Zhu Xianzhong. Design and Realization of Multimedia Document Structure of Internet TV[J]. 现代图书情报技术, 2015, 31(9): 82-89.
[13] Zhao Jingxian. Detect of Internet Fake Public Opinion Based on Decision Tree[J]. 现代图书情报技术, 2015, 31(6): 78-84.
[14] He Jianmin, Wang Zhe. The Pedigree Method to Mine Influential Clusters of Topic Information in Social Network[J]. 现代图书情报技术, 2015, 31(5): 65-72.
[15] Huang Wenbin, Xu Shanchuan, Ma Long, Wang Jun. Analysis of Mobile User Behaviors with Telecommunication Data[J]. 现代图书情报技术, 2015, 31(5): 80-87.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn