Personalized Information Recommendation System by Using Improved Adaptive Filtering Algorithm

In modernized information service environment, the user's information needs become more complicate and personalized with the highly obviously diversities among different users. In the background of the information society, it is becoming more and more important to put the personalized service into practice. An improved adaptive filtering algorithm based on vector space model was proposed in the paper. First, feature selection and pseudo feedback were used to select the initial filtering profiles and thresholds through training algorithm. Then user feedback was utilized to modify the profile and threshold adaptively through filtering algorithm. The algorithm had two advantages, the first was that it could carry on self- study to improve the precision; the second was that the execution did not need massive initial texts in the process of filtering.