The rapid growth of Internet users attracts advertisers to post their advertisements in Internet. The probabilistic selection algorithm was not satisfactory; while other advertising agents are unable to guarantee the quality due to insufficient and unstable user information. This paper describes a new advertising agent based on user information. The users' interests are discovered by the Order Pattern Mining algorithm first, then the Gaussian curve transformation is applied to represent their profiles. For the advertisements, we use the keywords from different categories to construct the advertisement profiles as Gaussian curves also. This allows us to select advertisements based on the intersections of the different profiles according to users' preferences in an effective and efficient mechanism. A prototype of the Intelligent Advertising Agent has been developed with Java and Oracle. From our evaluations, we observed that about 70% of the test cases are successful in making predictions which generated the most favorable category that the users are interested.