Improving case-based recommendation: A collaborative filtering approach

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2416, Issue , 2002, Pages 278-291

  O’Sullivan, Derry ^a   Wilson, David ^a   Smyth, Barry ^a  

^a UNIVERSITY COLLEGE DUBLIN   (Ireland)

Author keywords

[No Author keywords available]

Indexed keywords

CASE BASED REASONING; COLLABORATIVE FILTERING; RECOMMENDER SYSTEMS;

CASE BASED; ITEM SIMILARITY; SIMILARITY KNOWLEDGE;

DATA MINING;

EID: 84942754919     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Conference Paper

References (16)

1. Herlocker, J., Konstan, J., Borchers, A., Riedl, J.: An algorithmic framework for performing collaborative filtering. In: Proceedings of the 1999 Conference on Research and Development in Information Retrieval: SIGIR-99. (1999)
2. Konstan, J., Miller, B., Maltz, D., Herlocker, J., Gordon, L., Riedl, J.: Grouplens: Applying collaborative filtering to usenet news. Communications of the ACM 40 (1997) 77–87
3. Shardanand, U., Maes, P.: Social information filtering: Algorithms for automating “word of mouth”. In: Proceedings of ACM CHI’95 Conference on Human Factors in Computing Systems. (1995) 210–217
4. Smyth, B., Cotter, P.: Personalized electronic programme guides. Artificial Intelligence Magazine 21 (2001)
5. Good, N., Schafer, J.B., Konstan, J.A., Borchers, A., Sarwar, B.M., Herlocker, J.L., Riedl, J.: Combining collaborative filtering with personal agents for better recommendations. In: Proceedings of the 1999 Conference of the American Association of Artifical Intelligence (AAAI-99). (1999) 439–446
6. Soboroff, I., Nicholas, C.: Combining content and collaboration in text filtering. In: Proceedings of the IJCAI-99 Workshop on Machine Learning for Information Filtering. (1999)
7. Balabanovic, M., Shoham, Y.: Fab: Content-based, collaborative recommendation. Communications of the ACM 40 (1997) 66–72
8. Wilson, D.C., Leake, D.B.: Maintaining case-based reasoners: Dimensions and directions. Computational Intelligence 17 (2001)
9. Watson, I.: CBR is a methodology not a technology. Knowledge Based Systems 12 (1999) 303–308
10. O’Sullivan, D., Wilson, D., Smyth, B.: Using collaborative filtering data in case-based recommendation. In: Proceedings of the 15th International FLAIRS Conference. (2002) To Appear.
11. Fox, S., Leake, D.: Learning to refine indexing by introspective reasoning. In: Proceedings of First International Conference on Case-Based Reasoning, Berlin, Springer Verlag (1995) 431–440
12. Hipp, J., Nakhaeizadeh, U.G.: Mining association rules: Deriving a superior algorithm by analyzing today’s approaches. In: Proceedings of the 4th European Symposium on Principles of Data Mining and Knowledge Discovery. (2000)
13. Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A.I.: Fast discovery of association rules. In Fayyad, U.M., Piatetsky-Shapiro, G., Smyth, P., Uthurusamy, R., eds.: Advances in Knowledge Discovery and Data Mining. AAAI Press (1996) 307–328
14. Sarwar, B.M., Karypis, G., Konstan, J.A., Riedl, J.: Item-based collaborative filtering recommender algorithms. In: Proceedings of the Tenth InternationalWorldWideWeb Conference. (2001)
15. Donald, K.M.: (Use of the fischlar video library system)
16. Charu Aggarwal, Zheng Sun, P.S.Y.: Finding profile association rules (1998)