An Improved Apriori Algorithm for Association Rules of Mining

被引:6
|
作者
Wei Yong-qing [1 ]
Yang Ren-hua [2 ]
Liu Pei-yu [2 ]
机构
[1] Shandong Police Coll, Jinan 250014, Peoples R China
[2] Shandong Normal Univ, Sch Informat Sci & Engn, Jinan 250014, Peoples R China
来源
2009 IEEE INTERNATIONAL SYMPOSIUM ON IT IN MEDICINE & EDUCATION, VOLS 1 AND 2, PROCEEDINGS | 2009年
基金
中国国家自然科学基金;
关键词
D O I
10.1109/ITIME.2009.5236211
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Apriori -the classical association rules mining algorithm is a way to find out certain potential, regular knowledge from the massive ones. But there are two more serious defects in the data mining process. The first needs many times to scan the business database and the second will inevitably produce a large number of irrelevant candidate sets which seriously occupy the system resources. An improved method is introduced on the basic of the defects above. The improved algorithm only scans the database once, at the same time the discrete data and statistics related are completed, and the final one is to prune the candidate item sets according to the minimum supporting degree and the character of the frequent item sets. After analysis, the improved algorithm reduces the system resources occupied and improves the efficiency and quality.
引用
收藏
页码:942 / +
页数:2
相关论文
共 50 条
  • [21] MINING METALLOGENIC ASSOCIATION RULES COMBINING CLOUD MODEL WITH APRIORI ALGORITHM
    Ying, Cui
    He, Binbin
    Chen, Jianhua
    He, Zhonghai
    Yue, Liu
    2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, : 4507 - 4510
  • [22] Database encoding and an anti-Apriori algorithm for association rules mining
    Wang, Tong
    He, Pi-Lian
    PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2006, : 1195 - +
  • [23] An Improved Apriori Algorithm for Association Rule Mining in Employability Analysis
    Peng, Fang
    Sun, Yuhui
    Chen, Zigen
    Gao, Jing
    TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2023, 30 (05): : 1435 - 1442
  • [24] A Discovery for the Association Rules of Operation Sequence Based on Improved Apriori Algorithm
    Tan Yanhua
    2011 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION AND INDUSTRIAL APPLICATION (ICIA2011), VOL I, 2011, : 179 - 182
  • [25] A Discovery for the Association Rules of Operation Sequence Based on Improved Apriori Algorithm
    Tan Yanhua
    SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING: THEORY AND PRACTICE, VOL 2, 2012, 115 : 399 - 405
  • [26] A Discovery for the Association Rules of Operation Sequence Based on Improved Apriori Algorithm
    Tan Yanhua
    2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL VI, 2010, : 181 - 184
  • [27] Improvement of Apriori Algorithm for Association Rules
    Li, Xiaohui
    2011 INTERNATIONAL CONFERENCE ON FUTURE COMPUTER SCIENCE AND APPLICATION (FCSA 2011), VOL 4, 2011, : 312 - 315
  • [28] Improvement of Apriori Algorithm for Association Rules
    Li Xiaohui
    2012 WORLD AUTOMATION CONGRESS (WAC), 2012,
  • [29] Mining association rules between stroke risk factors based on the Apriori algorithm
    Li, Qin
    Zhang, Yiyan
    Kang, Hongyu
    Xin, Yi
    Shi, Caicheng
    TECHNOLOGY AND HEALTH CARE, 2017, 25 : S197 - S205
  • [30] The analysis on model of association rules mining based on concept lattice and Apriori algorithm
    Hu, XG
    Wang, DX
    Liu, XP
    Guo, J
    Wang, H
    PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, : 1620 - 1624