微信服务号

微信订阅号

2025-4-13- 3
Home > Archive>Volume 27, Issue 12, 2016 >3030-3050. DOI:10.13328/j.cnki.jos.004924
PDF HTML XML Export Cite reminder
Research on Multi-Scale Data Mining Method
Author:
Affiliation:

Fund Project:

National Natural Science Foundation of China (71271067); National Social Science Foundation of China (13BTY011, 13&ZD091)

  • Article
    • | |
  • Metrics
    • |
  • Reference
    • |
  • Related
    • |
  • Cited by
    • | |
  • Comments
    Abstract:

    Many researches of data mining have paid close attention to multi-scale theory. However the study of multi-scale data mining still comes short on universal theories and approaches. To overcome this limitation, this paper conducts a study of universal multi-scale data mining on theoretical and methodological aspect. First, the paper lays out the definition of data-scale-partition and data-scale based on concept hierarchy, and characterizes the relationship of upper-layer and lower-layer datasets between multi-scale datasets. Next, it illustrates the definition and essence of multi-scale data mining, and presents the classification of multi-scale data mining methods. Finally, it introduces the algorithm framework and its theoretical basis of multi-scale data mining, and proposes an algorithm named MSARMA (multi-scale association rules mining algorithm) to realize the transition of knowledge in multi-scale data expressions. Experiments are carried out to test MSARMA with the help of IBM T10I4D100K dataset and demographic dataset from H province, and the results indicate that MSARMA is effective and feasible with better coverage rate, better accuracy and lower average support error.

    Reference
    Related
    Cited by
    Comments
    Comments
    分享到微博
    Submit
Get Citation

柳萌萌,赵书良,韩玉辉,苏东海,李晓超,陈敏.多尺度数据挖掘方法.软件学报,2016,27(12):3030-3050

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:February 12,2015
  • Revised:September 25,2015
  • Online: December 08,2015
Links:Institute of Software, CASChina Computer FederationCASNSFC
You are the first2034790Visitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
Address：4# South Fourth Street, Zhong Guan Cun, Beijing 100190,Postal Code：100190
Phone：010-62562563 Fax：010-62562533 Email：jos@iscas.ac.cn
Technical Support：Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063