A model of user preference learning for content-based recommender systems

Computing and Informatics

Volumn 28, Issue 4, 2009, Pages 453-481

  Horváth, Tomáš ^a   Horv́th, Tomáš ^a  

^a P J AFÁRIK UNIVERSITY   (Slovakia)

Author keywords

Content based recommender systems; Induction of fuzzy and annotated logic programs; User preference learning

Indexed keywords

EID: 70350632424     PISSN: 13359150     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (46)

1. ABDI, H.: The Kendall Rank Correlation Coefficient. In N. J. Salkind (Ed.): Encyclopedia of Measurement and Statistics, Sage, Thousand Oaks (CA), 2007.
2. ADOMAVICIUS, G.-TUZHILIN, A.: Using Data Mining Methods to Build Customer Profiles. Computer, Vol. 34, 2001, No. 2, pp. 74-82.
3. *IA Conference, Pisa, 2003, Springer, LNAI, Vol. 2829, ISBN 978-3-540-20119-9, pp. 474-486.
4. BALABANOVIC, M.-SHOHAM, Y.: Fab: Content-Based, Collaborative Recommendation. Communications of the ACM archive, Vol. 40, Issue 3, 1997, ISSN 0001-0782, pp. 66-72.
5. BLOCKEEL, H.-DE RAEDT, L.-JACOBS, N.-DEMOEN, B.: Scaling up Inductive Logic Programming by Learning from Interpretations. Data Mining and Knowledge Discovery, Vol. 3, 1999, No. 1, ISSN 1384-5810, pp. 59-93.
6. BRANTING, L. K.-BROOS, P. S.: Automated Acquisition of User Preferences. International Journal of Human-Computer Studies, Vol. 46, 1997, pp. 55-77.
7. BURKE, R.:Hybrid Recommender Systems: Survey and Experiments. User Modeling and User-Adapted Interaction, Vol. 12, 2002, No. 4, ISSN 0924-1868, pp. 331-370.
8. CRANE, M.: Efficiently Learning Trends in User Preferences. Poster at Computer Science 294, Practical Machine Learning, Fall 2006.
9. DASTANI, M.-JACOBS, N.-JONKER, C. M.-TREUR, J.: Modelling User Preferences and Mediating Agents in Electronic Commerce. Lecture Notes in Computer Science, Vol. 1991, ISBN 3-540-41671-4, pp. 163-193, Springer 2001.
10. DELGADO, J.-ISHII, N.: Formal Models for Learning of User Preferences, a Preliminary Report. In: Proceedings of the IJCA99 Workshop on Learning about Users, Stockhpm 1999, pp. 13-20.
11. DELGADO, J.-ISHII, N.: On-line Learning of User Preferences in Recommender Systems. In: Proceedings of the IJCAI-99 Workshop on Machine Learning for Information Filtering, 1999.
12. th WEBKDD Workshop, Seattle, 2004.
13. DžEROSKI, S.-LAVRAČ, N.: An Introduction to Inductive Logic Programming. Relational data mining, Springer, 2001, ISBN 3-540-42289-7, pp. 48-73.
14. ECKHARDT, A.-HORVÁTH, T.-VOJTÁŠ, P.: PHASES: A User Profile Learning Approach for Web Search. In: Proceedings of the 2007 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2007), Silicon Valley, USA, IEEE Computer Society, 2007, ISBN 0-7695-3026-5, pp. 780-783.
15. st International Conference on Scalable Uncertainty Management, (SUM'07), Washington DC, USA, Lecture Notes in Artificial Intelligence, Vol. 4772, 2007, ISSN 0302-9743, ISBN 978-3-540-75407-7, pp. 116-130, Springer, 2007.
16. GOERGE, T.-MERUGU, S.: A Scalable Collaborative Filtering Framework Based on Co-clustering. In: Proceedings of the Fifth IEEE International Conference on Data Mining, 2005, ISBN 1550-4786, pp. 625-628.
17. th International Conference on Intelligent User Interfaces (IUI), Santa Fe, New Mexico, ACM, 2001, ISBN 1-58113-325-1, pp. 87-90.
18. GRČAR, M.-FORTUNA, B.-MLADENIČ, D.-GROBELNIK, M.: kNN Versus SVM in the Collaborative Filtering Framework. Data Science and Classification, ISBN 9783-540-34415-5, pp. 251-260, Springer, 2006.
19. GUO, Y.-MULLER, J. P.-WEINHARDT, C.: Learning User Preferences for Multiattribute Negotiation: An Evolutionary Approach. In: Proceedings of CEEMAS 2003, LNAI 2691, pp. 303-313, Springer, 2003.
20. GURSKý, M.-HORVÁTH, T.-NOVOTNý, R.-VANEKOVÁ, V.-VOJTÁŠ, P.: UPRE: User Preference Based Search System. In: Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI'06), Hong Kong, 2006, IEEE Computer Society, 2006, ISBN 0-7695-2747-7, pp. 841-844.
21. th Conference Znalosti'05, Stará Lesná, Slovakia, 2005: FEI VB-TU Ostrava, Czech Republic, 2005, ISBN 80-248-0755-6, pp. 194-201.
22. HAWKINS, R.: Ranking and Scoring-Guidelines. Manual, ICRA Learning Resources.
23. th IFIP International Conference on Information Technology for Balanced Automation Systems in Manufacturing and Services, Vienna, Austria, 2004, Springer, IFIP International Federation For Information Processing (Vol. 159), 2004, ISSN 15715736, ISBN 0-387-22828-4, pp. 451-458.
24. th European Conference on Machine Learning and the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD'04), Pisa, Italy, 2004, TU Darmstadt (J. Fuernkranz, Ed.), Darmstadt, Germany, 2004, pp. 46-63.
25. HORVÁTH, T.-VOJTÁŠ, P.: Ordinal Classification with Monotonicity Constraints. In: Proceedings of the 6th Industrial Conference on Data Mining (ICDM'06), Leipzig, Germany, 2006, Springer-Verlag, Lecture Notes in Artificial Intelligence (Vol. 4065), 2006, ISSN 0302-9743, ISBN 3-540-36036-0, pp. 217-225.
26. th International Conference on Inductive Logic Programming (ILP'06), Santiago de Compostela, Spain, 2006, Springer-Verlag, Lecture Notes in Artificial Intelligence, Vol. 4455, 2007, ISSN 0302-9743, ISBN 978-3-54073846-6, pp. 260-274.
27. rd International Conference on Machine Learning, ISBN 1-59593-383, Pittsburgh, PA 2006, pp. 273-280.
28. JUNG, S. Y.-HONG, J. H.-KIM, T. S.: A Statistical Model for User Preference. IEEE Transactions on Knowledge and Data Engineering, Vol. 17, 2005, No. 6, pp. 834-843.
29. KANG, S.-LIM, J.-KIM, M.: Statistical Inference Method of User Preference on Broadcasting Content. In: Proceedings of ICCS 2005, Springer, LNCS 3514, 2005, pp. 971-978. (Pubitemid 41342895)
30. KIFER, M.-SUBRAHMANIAN, V. S.: Theory of Generalized Annotated Logic Programming and Its Applications. J. Logic Programming, Vol. 12, 1992, pp. 335-367.
31. KOBSA, A.: Generic User Modeling Systems. The adaptive web: Methods and strategies of web personalization, Heidelberg, Germany, Springer, LNCS 4321, ISBN 9783-540-72078-2, pp. 136-154.
32. LEITE, J.-BABINI, M.: Dynamic Knowledge Based User Modeling for Recommender Systems. In: Proceedings of the ECAI 2006 Workshop on Recommender Systems, Riva del Garda, Italy, 2006, pp. 134-138.
33. METEREN, R. V.-SOMEREN, M. V.: Using Content-Based Filtering for Recommendation. MLnet/ECML 2000 Workshop, May 2000, Barcelona, Spain.
34. The NAZOU project. http://nazou.fiit.stuba.sk.
35. PAZZANI, M.-BILLSUS, D.: Learning and Revising User Profiles: The Identification of Interesting Web Sites. Machine Learning, Vol. 27, 1997, pp. 313-331.
36. th International Conference on Intelligent User Interfaces IUI'02, ISBN 1-58113-459-2, pp. 127-134.
37. SRINAVASAN, A.: The Aleph Manual. Technical Report, Comp. Lab., Oxford University.
38. rd Workshop on Intelligent Techniques for Web Personalization, in conjunction with IJCAI'05, Edinburgh, Scotland, 2005.
39. TASCHUK, M.: A Hybrid Knowledge-based/Content-based Recommender System in the Bluejay Genome Browser. Undergraduate Honours Thesis, Faculty of Medicine at the University of Calgary, 2007.
40. TOWLE, B.-QUINN, C.: Knowledge Based Recommender Systems Using Explicit User Models. Knowledge-based Electronics Markets, papers from the AAAI Workshop, AAAI Technical Report WS-00-04, AAAI Press, pp. 74-77.
41. ASUNCION, A.-NEWMAN, D. J.: UCI Machine Learning Repository. http://www.ics.uci.edu/~mleaxn/MLRepository.html. Irvine, CA, 2007, University of California, School of Information and Computer Science.
42. XU, J. A.-ARAKI, K.: A Personalized Recommendation System for Electronic Program Guide. In: Proceedings of AI 2005, Springer, LNAI 3809, 2005, pp. 1146-1149. (Pubitemid 43987282)
43. YU, Z.-ZHOU, X.-YANG, Z: A Hybrid Learning Approach for TV Program Personalization. In: Proceedings of KES 2004, Springer, LNAI 3213, 2004, pp. 630-636.
44. VOJTÁŠ, P.: Fuzzy Logic Programming. Fuzzy Sets and Systems, Vol. 124, 2004, No. 3, pp. 361-370.
45. VOJTÁŠ, P.-VOMLELOVÁ, M.: Transformation of Deductive and Inductive Tasks Between Models of Logic Programming With Imperfect Information. In: Proceedings of IPMU, 2004, Roma, Italy, pp. 839-846.
46. VOJTÁŠ, P.-VOMLELOVÁ, M.: On Models of Comparison of Multiple Monotone Classifications. In: Proc. IPMU 2006, Paris, France, Editions EDK, Paris, pp. 1236-1243.