臺灣博碩士論文加值系統

近年來網際網路已成為訊息交換與訊息傳遞的媒介。傳統的消費行為也因應這樣的趨勢，因此傳統的商務行為也演進到電子商務的領域。在這樣的環境下商家必須清楚的知道消費者的喜好以增加商家的利益。所以提供一個推薦服務即是一個重要的議題。我們會分析使用者的行為與喜好來得到消費者、產品與產品特性之間的關係並根據這些分析結果建議適當的產品或訊息。另一方面自動協商也是一個在電子商務上的重要課題。當使用者參與於商務的行為時，使用者會與商家根據他們的條件來作協商的動作並得到對使用者最有利的結果。因此本論文整合推薦與協商的機制在電子商務環境上。此外這樣的工作對使用者來說是一個複雜與困難的工作，因此本論文利用智慧型代理人技術的優點來作為設計的方法。因此這個整合的系統將會是未來電子商務上的一個重要的應用。

The Internet has become a popular medium for information exchange and knowledge delivery. Traditional buying and selling activities also follow the trend, therefore the commerce activities have moved to electronic commerce. However, even with the advents of the World Wide Web, online merchants must know what users want and to increase the sales revenue. So, providing recommendation services is an important strategy for the merchants. We analyze users’ on-line behavior and interests, and recommend to them new or potential products and the analysis mechanism is based on the correlation among customers, product items, and product features. On the other hand the negotiation is another issue in electronic commerce. When parties participate the business activities, they would negotiate with each other to make the best gain with their purpose. We use the multi-attribute utility theory to design the negotiation process. Hence, we combine the negotiation and recommendation service and propose the integrated system to serve users. But these kinds of task are hard to process for users, so we take advantage of intelligent software agent technology to develop the system and the integrated system will play an important application in the future commerce activities.

Chapter 1 Introduction.........................................1
1.1 Motivation..............................................1
1.2 Intelligent Agent Technology and Electronic Commerce....3
1.3 Overview................................................4
Chapter 2 Related Work.........................................6
2.1 Electronic commerce.....................................6
2.2 Recommendation system..................................10
2.3 Negotiation System.....................................14
2.4 Intelligent Software Agent.............................16
Chapter 3 The Customer-Product-Feature Model..................20
3.1 Customer Behavior Record...............................21
3.2 Customer-Product Matrix................................22
3.3 Product-Feature Matrix.................................23
3.4 Customer-Feature Matrix................................25
Chapter 4 The Design of Recommendation Engine.................29
4.1 Recommendation Algorithms..............................29
4.2 Recommendation Events..................................36
4.3 Measurement and Discussion.............................40
Chapter 5 Mobile Agent Framework for Electronic Commerce......45
5.1 Hierarchy of Mobile Agent Platform.....................45
5.2 Collaborative Agent Architecture of Recommendation Application...................................................48
5.3 Community Recommendation...............................51
Chapter 6 Integrated Negotiation Agent System.................60
6.1 The Design of Negotiation Engine.......................60
6.1.1 The Components of Negotiation.....................60
6.1.2 The Computation of Negotiation Strategy...........62
6.2 Negotiation Protocol...................................65
6.2.1 The Message Flow of the Negotiation...............65
6.2.2 The Decision Making Machine.......................67
6.3 System Architecture....................................71
6.4 The Integration of Negotiation and Recommendatio.......76
Chapter 7 Conclusions and Further Research....................78
7.1 Conclusions............................................78
7.2 Further Research.......................................80
Bibliography..................................................81
Appendix A. "Recommendation Systems use The CPF model in EC," Accepted by the Industry Management and Data Systems.(EI).....87
Appendix B. "A Practical Approach for Mobile Recommendation Agents over the Internet," in Proceedings of the 2001 IEEE International Conference on Multimedia and Expo (ICME2001)...119

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