The key to personalized search engine lies in user model. Traditional personalized model results in that the search results of secondary search are partial to the long-term interests, besides, forgetting to the long-term interests disenables effective recollection of user interests. This paper presents a quaternary-stage user interest model based on user browsing behavior and web page classification, which consults the principles of cache and recycle bin in operating system, by setting up an illuminating text-stage and a recycle bin interest-stage in front and rear of the traditional interest model respectively to constitute the quaternary-stage user interest model. The model can better reflect the user interests, by using an adaptive natural weight and its calculation method, and by efficiently integrating user browsing behavior and web document content.