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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.

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