Improvement of Web Data Mining Method and its Application in Personalized Recommendation

Personality recommendation system in digital library has good development and applied prospects. It is becoming gradually an important research content in an electronic resources intelligent processing. This study proposes a WEB data mining method based on the improvement of genetic algorithm. At the same time, this method is applied to the digital library electronic resources in personalized recommendation. The experimental results show that the method is suitable for large-scale text data set. This method in classification accuracy is higher and classification is faster. The method greatly improves the text mining system classification efficiency.