English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 63911/96578 (66%)
造访人次 : 3970592      在线人数 : 165
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/65018


    题名: Rough-Set-Based Association Rules Applied to Brand Trust Evaluation Model
    作者: Liao, Shu-hsien;Lin, Hwei-jen
    贡献者: 淡江大學經營決策學系
    关键词: Machine Learning;Knowledge Representation;Knowledge-Based Systems;Rough sets;Association rules
    日期: 2010
    上传时间: 2013-03-12 11:00:49 (UTC+8)
    出版者: Heidelberg: Springer
    摘要: The Internet has emerged as the primary database, and technological platform for electronic business (EB), including the emergence of online retail concerns. Knowledge collection, verification, distribution, storage, and re-use are all essential elements in retail. They are required for decision-making or problem solving by expert consultants, as well as for the accumulation of customers and market knowledge for use by managers in their attempts to increase sales. Previous data mining algorithms usually assumed that input data was precise and clean, this assumes would be eliminated if the best rule for each particular situation. The Algorithm we used in this study however, proved to function even when the input data was vague and unclean. We provided an assessment model of brand trust as an example, to show that the algorithm was able to provide decision makers additional reliable information, in the hope of building a rough set theoretical model and base of resources that would better suit user demand.
    關聯: Lecture Notes in Computer Science 6443, p.634-641
    DOI: 10.1007/978-3-642-02568-6_9
    显示于类别:[管理科學學系暨研究所] 期刊論文
    [資訊工程學系暨研究所] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    index.html0KbHTML59检视/开启
    Rough Sets Based Association Rules Application for Knowledge-Based System Design.pdf309KbAdobe PDF54检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈