Abstract

With the rapid growth of network information, information filtering technology is more widely used. This paper discusses the content-based filtering and collaborative filtering, and proposes a hybrid filtering model with these two methods in order to overcome their own shortages. In this hybrid filtering method, genetic algorithm is used to generate initial profiles on server-side, and particle swarm optimization is used to update the profiles with the information from users. This approach is feasible from the theoretical analysis and the experiment in Chinese data set.

Key words: Information filtering, content-based filtering, collaborative filtering, particle swarm optimization, genetic optimization.