A Research on Personalized Recommendation Based on Web Log Mining

Web log mining is an important research field of Web data mining. Personalized service is the center of Web log mining applications. Based on the study of Web log mining and personalized service, this article established a personalization recommendation model in the basis of Web log mining. It presented similar Apriori algorithm based on constraints. It exploited and generated personalization recommendation candidate sets reflecting users' behavior characteristics and demands practically. Then the personalization recommendation model underwent a simulation. The results showed improved similar Apriori algorithm was of practical value to personalization recommendation. Improved similar Apriori algorithm could effectively provided users with intelligent navigation service and offer references to dynamic adjustments of content and structure of web pages.