User Profile Creation Using Genetic Algorithm with Kullback Leibler Divergence

Abstract

In this paper we propose a user profile creation method using the Kullback Leibler divergence. To cope with information flood, many information filtering systems have been developed up to now. In the information filtering systems it is important to create a user profile which represents user's interests correctly. Since almost all information filtering systems are developed with techniques of information retrieval, machine learning, and pattern recognition, they often use a linear function as a discriminant function. To classify information in the field of document classification more precisely, the systems have been reported which use a non-linear function as a discriminant function. The proposed method is to use the Kullback Leibler divergence as a discriminant function which denotes to user's interest in the information filtering system. To identify an optimal discriminat function with documents which a user evaluates, we use the real-coded genetic algorithm. We compare the present method with the other one using a linear discriminant function and confirm the effectiveness of the proposing method.