中大機構典藏-NCU Institutional Repository-提供博碩士論文、考古題、期刊論文、研究計畫等下載:Item 987654321/51855
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 80990/80990 (100%)
Visitors : 42801949      Online Users : 1090
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version


    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/51855


    Title: Mining negative generalized knowledge from relational databases
    Authors: Wu,YY;Chen,YL;Chang,RI
    Contributors: 資訊管理學系
    Keywords: ATTRIBUTE-ORIENTED INDUCTION;ASSOCIATION RULES;DISCOVERY;REDUCTION
    Date: 2011
    Issue Date: 2012-03-27 19:07:44 (UTC+8)
    Publisher: 國立中央大學
    Abstract: Attribute-oriented induction (AOI) is a useful data mining method for extracting generalized knowledge from relational data and users' background knowledge. Concept hierarchies can be integrated with the AOI method to induce multi-level generalized knowledge. However, the existing AOI approaches are only capable of mining positive knowledge from databases; thus, rare but important negative generalized knowledge that is unknown, unexpected, or contradictory to what the user believes, can be missed. In this study, we propose a global negative attribute-oriented induction (GNAOI) approach that can generate comprehensive and multiple-level negative generalized knowledge at the same time. Two pruning properties, the downward level closure property and the upward superset closure property, are employed to improve the efficiency of the algorithm, and a new interest measure, nim(cl), is exploited to measure the degree of the negative relation. Experiment results from a real-life dataset show that the proposed method is effective in finding global negative generalized knowledge. (C) 2010 Elsevier B.V. All rights reserved.
    Relation: KNOWLEDGE-BASED SYSTEMS
    Appears in Collections:[Department of Information Management] journal & Dissertation

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML666View/Open


    All items in NCUIR are protected by copyright, with all rights reserved.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明