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With the advance of information technology, people could retrieve and manage their information more easily. However, the information users are still confused of information overloading problem. The recommendation system is designed based on personal preferences. It can recommend the fittest information to users, and it would help users to obtain in-formation more conveniently and quickly. In our research, we design a recommendation system based on personal ontology and collaborative filtering technologies. Personal ontology is constructed by Formal Concept Analysis (FCA) algorithm and the collaborative filtering is design based on ontology similarity comparison among users. In order to evaluate the performance of our recommendation system, we have conducted an experiment to estimate the users’ satisfaction of our experiment system. The results show that, combining collaborative filtering technology with FCA in a recommendation system can get better users’ satisfaction

Combining Personal Ontology and Collaborative Filtering to Design a Document Recommendation System