Web page recommendation based on semantic web usage mining

摘要: The growth of the web has created a big challenge for directing user to Web pages in their areas interest. Meanwhile, usage mining plays an important role finding these interest based on user's previous actions. extracted patterns are useful various applications such as recommendation. Classical does not take semantic knowledge and content into pattern generations. Recent researches show that ontology, background knowledge, can improve pattern's quality. This work aims design hybrid recommendation system integrating information with page clustering similarity. Since seen ontology individuals, frequent navigational form instances instead addresses, is done using result used generating recommendations users. recommender engine presented this paper which clustering, creates list appropriate recommendations. results implementation indicate access sequence yields more accurate