Information Recommendation and Knowledge Maintenance for Electronic Commerce

• Main Authors: Huang, Shiu-Li, 黃旭立
• Other Authors: Lin, Fu-Ren
• Format: Others
• Language: en_US
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/60435584285985646383

碩士 === 國立中山大學 === 資訊管理學系 === 87 === This research employs data mining and intelligent agent techniques to develop a satisfactory information recommendation system for electronic commerce. This system recommends information by using association analysis and applies backpropagation neural network to maintain the discovered rules. We also construct a measuring instrument to evaluate user information satisfaction (UIS) on the Internet. The experiment results reveal that the system increases user satisfaction significantly. The incremental mining method proposed by this research is efficacious to tackle knowledge contradiction and integration problems and the new UIS measuring instrument has high validity and reliability. These methods and techniques all can be applied to search engines and electronic stores actually.