臺灣博碩士論文加值系統

Internet advertising such as Web advertising and targeted advertising is currently the major source of revenue in electronic commerce. Web advertising in general places advertisements on the Web sites, while targeted advertising is more focused on delivering appropriate advertisements according to each user’s preferences and interests. It is believed that targeted advertising will be the driving force for the next phase of electronic commerce. The purpose of this study is to design an agent-based targeted advertising system using a two-phase information filtering approach that integrates user stereotypes. Information filtering and user stereotypes can help us to decide which advertisement to deliver whereas software agents are capable of automating the whole targeted advertising process. The two-phase information filtering approach also combines a rating scheme in which users and objects are represented using Gaussian curves. A prototype of an agent-based targeted advertising system is implemented and simulation conducted.

ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi

CHAPTER
I. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.4 Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

II. LITERATURE REVIEW . . . . . . . . . . . . . . . . . . . . . . . 4
2.1 Internet advertising . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1.1 Definition . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1.2 Internet advertising models . . . . . . . . . . . . . . . 5
2.2 Targeted Advertising . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2.1 Benefits . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2.2 Targeting technologies . . . . . . . . . . . . . . . . . . 7
2.3 Information Filtering . . . . . . . . . . . . . . . . . . . . . . . 8
2.3.1 Definition . . . . . . . . . . . . . . . . . . . . . . . . 8
2.3.2 Filtering approaches . . . . . . . . . . . . . . . . . . . 8
2.3.3 A generic model of IF systems . . . . . . . . . . . . . 10
2.4 Software Agents . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.4.1 Definition and characteristics . . . . . . . . . . . . . . 11
2.4.2 Architecture . . . . . . . . . . . . . . . . . . . . . . . 13
2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

III. Model Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.1 The filtering approach for targeted advertising . . . . . . . . . 16
3.2 The GRAS algorithm . . . . . . . . . . . . . . . . . . . . . . . 18
3.2.1 Profile generation and adaptation . . . . . . . . . . . 23
3.3 A targeted advertising model . . . . . . . . . . . . . . . . . . . 26
3.4 An agent-based system architecture . . . . . . . . . . . . . . . 29
IV. Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
4.1 Overview of system implementation . . . . . . . . . . . . . . . 32
4.1.1 Developing an agent-based application . . . . . . . . . 33
4.2 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
4.2.1 Object and user profiles . . . . . . . . . . . . . . . . . 35
4.2.2 Assumptions and limitations . . . . . . . . . . . . . . 36
4.2.3 Implementation of the prototype system. . . . . . . . 37
V. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
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