A Framework for Enterprise Knowledge Discovery by Association Mining from Databases

• Main Authors: Wen-Jie Lee, 李文傑
• Other Authors: Shang-Wei Changchien
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/47784192599849293758

碩士 === 朝陽科技大學 === 資訊管理系碩士班 === 91 === In recent years，database data mining has becoming an emerging research area，which attracts great attention of numerous researchers. Although there were successful applications in various areas in the industry，the existing database data mining methods are more theoretical than practical. To perceive business problems from a manager’s problem solving perspective，and transform the operational or managerial problems into the corresponding data mining tasks，it requires insight of business domain processes and problems，and expertise of database data mining methods. This research therefore proposes a practical enterprise database knowledge discovery framework，which consists of six major steps as follows：1.Search subjects/problems；2.Investigate subjects/problems；3.Define mining tasks；4.Perform data mining；5.Assess mined rules；6.Update knowledge base. According to the case study，to which the proposed enterprise database knowledge discovery framework was successfully applied，it is proved that the proposed framework can efficiently assist an enterprise in investigating current problems/interesting subjects，and discovering specific knowledge for supporting enterprise decision making.