Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/1089551.1089634acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicecConference Proceedingsconference-collections
Article

Research and implementation on datamining applied to learning guidance system

Published: 15 August 2005 Publication History

Abstract

Datamining become an important field of research. However, there is an important challenge to applying the technique to real-world applications. An integrated datamining system for learning guidance is presented in this paper. It presented the datamining process in detail. More importantly, it puts forward a new enhanced method to improve the mining efficiency. Datamining applied to learning guidance provides a scientific basis for college management and decision-making.

References

[1]
Agrawal R, Imielinski T, Swami A. Mining Association Rules between Sets of Items in Large Database {M}. In SIGMOD' 93, Washington, DC,(May 1993), 207--216.
[2]
Savasere A. Omiecinski E, Navathe S. An efficient algorithm for Mining association rules{c}.In:Proceedings of the 21th International Conference on Very large DataBase, Zurich, Switzerland,(1995-09), 432--444.
[3]
John D. Holt, Soon M. Chung. Mining association rules using inverted hashing and pruning{J} Information processing letter .83(2002), 211--220
[4]
Mararet H. Dunham. DATA MINING Introductory and Advanced Topics.{M} Tsinghua University. BeiJing.2003. 184--187
[5]
Jyh-Bin Yang. A rule induction-based knowledge system for retaining wall selection. Expert system with applications. {J} 2002.273--279

Index Terms

  1. Research and implementation on datamining applied to learning guidance system

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ICEC '05: Proceedings of the 7th international conference on Electronic commerce
    August 2005
    957 pages
    ISBN:1595931120
    DOI:10.1145/1089551
    • Conference Chairs:
    • Qi Li,
    • Ting-Peng Liang
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 15 August 2005

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. apriori algorithm
    2. association rule
    3. datamining

    Qualifiers

    • Article

    Acceptance Rates

    Overall Acceptance Rate 150 of 244 submissions, 61%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • 0
      Total Citations
    • 914
      Total Downloads
    • Downloads (Last 12 months)1
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 29 Sep 2024

    Other Metrics

    Citations

    View Options

    Get Access

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media