ABSTRACT 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.
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nullD. CHEN and Y. CHIANG, "Combining Personal Ontology and Collaborative Filtering to Design a Document Recommendation System," Journal of Service Science and Management, Vol. 2 No. 4, 2009, pp. 322-328. doi: 10.4236/jssm.2009.24038.
 B. Sarwar, J. Konstan, A. Borchers, J. Herlocker, B. Miller, and J. Riedl, “Using Filtering Agents to Improve Prediction Quality in the GroupLens Research Collaborative Filtering System,” Proceedings of the 1998 Conference on Computer Supported Cooperative Work, pp. 345–354, 1998.
M. Balabanovic and Y. Shoham, “Fab: Content-Based, Collaborative Recommendation,” Communications of the ACM, Vol. 40, pp. 66–72, 1997.
J. B. Schafer, J. Konstan, and J. Riedl, “Recommender System in E-Commerce,” Proceedings of the first ACM Conference on Electronic Commerce, pp. 158–166, 1999.
 S. Staab, and H. Werthner, “Intelligent Systems for Tourism,” IEEE Intelligent Systems, Vol. 17, pp. 53–66, 2002.
 L. Khan, D. McLeod, and E. Hovy, “Retrieval Effectiveness of an Ontology-based Model for Information Selection,” Very Large Data Bases, Vol. 13, pp. 71–85, 2004.
 H. M. Haav, “A semi-automatic method to ontology design by using FCA,” Proceedings of the 2nd International CLA Workshop, Ostrava, pp. 13–25, 2004.
C. H. Hsu, “Automatically Constructing Ontology on Semantic Web,” M.S. thesis, Fu Jen Catholic University, Taiwan, 2004.
 M. Obitko, V. Snasel, J. Smid, and V. Snasel, “Ontology Design with Formal Concept Analysis,” In V. Snasel, and R. Belohlavek, (eds.) Concept Lattices and their Applications, Ostrava: Czech Republic, pp. 111–119, 2004.
G. Stumme, and A. Maedche, “FCA-MERGE: bottom-up merging of ontologies,” Proceedings of the Seventeenth International Conference on Artificial Intelligence, pp. 225–234, 2001.
 Y. Zhao, X. Wang, and W. Halang, “Ontology Mapping based on Rough Formal Concept Analysis,” Proceedings of the Advanced International Conference on Telecommunications and International Conference on Internet and Web Applications and Services, pp. 180, 2006.
 B. Ganter, and R. Wille, “Applied lattice theory: Formal Concept Analysis,” In G. Grater, (edition), General Lattice Theory, Springer, Berlin, 1997.
 G. Schreiber, B. Wielinga, and W. Jansweijer, “The kactus view on the “o” word,” Workshop on basic ontological issues in knowledge sharing: international joint conference on artificial intelligence, pp. 159–168, 1995.
A. Bernaras, I. Laresgoiti, and J. Corera, “Building and reusing ontologies for electrical network applications,” Proceedings of European Conference on Artificial Intel-ligence, pp. 298–302, 1996.
S. William and T. Austin, “Ontologies,” IEEE Intelligent systems, Vol. 14, pp. 18–19, 1999.
B. Chandrasekaran, J. R. Josephson, and V. R. Benjamins, “What are ontologies, and why do we need them?” IEEE Intelligent systems, Vol. 14, pp. 20–26, 1999.
J. Chaffee and S. Gauch, “Personal Ontologies for Web
Navigation,” Proceedings of Conference on Information Knowledge Management, pp. 227–234, 2000.
 R. Wille, “Restructuring lattice theory: An approach based on hierarchies of concepts,” In I. Rival, (edition) Ordered Sets, Reidel, Boston-Dordrecht, pp. 445–470, 1982.
 A. Formica, “Ontology-based concept similarity in Formal Concept Analysis,” Information Sciences, Vol. 176, pp. 2624–2641, 2006.
K. E. Wolff, “A first course in Formal Concept Analysis - how to understand line diagrams,” Advances in Statistical Software, Vol. 4, pp. 429–438, 1994.
 P. Cimiano, A. Hotho, G. Stumme, and J. Tane, “Concept Knowledge Processing with Formal Concept Analysis and Ontologies,” Proceedings of Second International Conference on Formal Concept Analysis, pp. 189–207, 2004.
 W. H. Delone and E. R. Mclean, “Information System Success: The Quest for the Dependent Variable,” Information Systems Research, Vol. 3, pp. 60–95, 1992.
 H. D. William and R. M. Ephraim, “Information Systems Success: The quest for the dependent variable,” Information Systems Research, Vol. 3, pp. 60–95, 1992.