Probabilistic Selection Algorithm Research Articles

AN INTELLIGENT AGENT FOR WEB ADVERTISEMENTS

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.

General performance analysis of key-to-address transformation methods using an abstract file concept

This paper presents a new approach to the analysis of performance of the various key-to-address transformation methods. In this approach the keys in a file are assumed to have been selected from the key space according to a certain probabilistic selection algorithm. All files with the same number of keys selected from this key space will be suitably weighted in accordance with the algorithm, and the average performance of the transformation methods on these files will be used as the potential of these methods. Using this analysis, methods with the same overall performance can be classified and key distributions partial to certain transformations can be identified. All this can be done analytically. The approach is applied to a group of transformation methods using files whose keys are selected randomly.