淡江大學機構典藏:Item 987654321/4411
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62797/95867 (66%)
Visitors : 3734624      Online Users : 411
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU 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: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/4411


    Title: Mapping knowledge to rules for scheduling expert systems
    Authors: 劉艾華;Liou, Ay-hwa Andy;Wu, Ming-tser
    Contributors: 淡江大學資訊管理學系
    Date: 1996
    Issue Date: 2009-03-19 13:34:25 (UTC+8)
    Publisher: Kidlington: Pergamon Press
    Abstract: Although the theoretical framework of expert systems has been well established, the process of developing a non-trivial expert system is still considered a difficult task. The main reason for this is that the nature of expert systems is knowledge-intensive. Also, it is usually difficult for domain experts to explain or communicate their expertise to the system professionals. Many methodologies have been proposed to overcome this domain knowledge representation problem. Most of them require the assistance of an expert system shell (tool). However, with a purpose of helping the system development in mind, most of them were not satisfactory. This research takes the experience of implementing a course scheduling expert system, and suggests two analysis methods to describe the characteristics of course scheduling knowledge. It is shown that these methods provide assistance on clarifying the complicated scheduling problem. Another favorable advantage of this method is its capability helping the transferring of domain knowledge to rules in the knowledge base.
    Relation: Expert systems with Applications 10(3-4), pp.341-350
    DOI: 10.1016/0957-4174(96)00012-7
    Appears in Collections:[Graduate Institute & Department of Information Management] Journal Article

    Files in This Item:

    File Description SizeFormat
    0957-4174_10(3-4)p341-350.pdf827KbAdobe PDF418View/Open
    Mapping knowledge to rules for scheduling expert systems.pdf827KbAdobe PDF1View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


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