To provide the personalized services for learners according to user's learning behavior, firstly, through theory of Fuzzy Ontology, the ambiguity and uncertainty of information in E-learning recommendation system was analyzed, and fuzzy information was extended to the ontology. Secondly, the user interest estimation based on behavior was studied in term of user's learning preferences and cognitive status, user profile was described by the learning object, and then a user model updating

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... was proposed. Finally, a fuzzy recommendation system based on user profile was built. As verified by experiment, the results have shown that the system can provided the personalized learning services according to user's learning behavior, and it is useful in describing user preferences. According to the definition of Anaya [7], the recommended system was system which can output the personalized recommendation content, and can provide the interesting, personalized and useful object in the optional space for users. So, the components of user profile based on fuzzy ontology and the automatic construction process was introduced, of which user profile was a description file of the user's interest, was an embodiment of the user's personalized needs, and also was a relevant learning object composition [8] .