Collaborative filtering for Orkut communities: Discovery of user latent behavior

WWW'09 - Proceedings of the 18th International World Wide Web Conference

Volumn , Issue , 2009, Pages 681-690

  Chen, Wen Yen ^a   Chu, Jon Chyuan ^b   Luan, Junyi ^c   Bai, Hongjie ^d   Wang, Yi ^d   Chang, Edward Y ^d  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c PEKING UNIVERSITY   (China)

^d Google Inc   (Japan)

Author keywords

Association rule mining; Collaborative filtering; Data mining; Latent topic models; Recommender systems

Indexed keywords

COLLABORATIVE FILTERING; DATA SETS; EMPIRICAL COMPARISON; LATENT DIRICHLET ALLOCATIONS; LATENT INFORMATION; LATENT STRUCTURES; LATENT TOPIC MODEL; NETWORKING SERVICES; OBSERVED DATA; ONLINE INTERACTION; PARALLEL IMPLEMENTATIONS;

DATA MINING; RECOMMENDER SYSTEMS; STATISTICS; WORLD WIDE WEB;

BEHAVIORAL RESEARCH;

EID: 77954593787     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1526709.1526801     Document Type: Conference Paper

References (20)

1. Open source parallel lda. http://code.google.com/p/plda/.
2. R. Agrawal, T. Imieliński, and A. Swami. Mining association rules between sets of items in large databases. In Proc. of the 1993 ACM SIGMOD conference, pages 207-216, 1993.
3. R. Agrawal and R. Srikant. Fast algorithms for mining association rules in large databases. In Proc. of the 20th VLDB conference, pages 487-499, 1994.
4. D. M. Blei and M. I. Jordan. Modeling annotated data. In Proc. of the 26th ACM SIGIR conference, pages 127-134, New York, NY, USA, 2003.
5. D. M. Blei, A. Y. Ng, and M. I. Jordan. Latent Dirichlet allocation. Journal of Machine Learning Research, 3:993-1022, 2003.
6. J. Dean and S. Ghemawat. Mapreduce: simplified data processing on large clusters. Communications of the ACM, 51(1):107-113, 2008.
7. T. L. Griffiths and M. Steyvers. Finding scientific topics. Proceedings of the National Academy Science, 101 (suppl. 1):5228-5235, April 2004.
8. W. Gropp, E. Lusk, and A. Skjellum. Using MPI-2: Advanced Features of the Message-Passing Interface. MIT Press, 1999.
9. J. Han, J. Pei, Y. Yin, and R. Mao. Mining frequent patterns without candidate generation: A frequent-pattern tree approach. Data Min. Knowl. Discov., 8(1):53-87, 2004.
10. K. Järvelin and J. Kekäläinen. Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems, 20(4):422-446, 2002.
11. Y. Koren. Factorization meets the neighborhood: a multifaceted collaborative filtering model. In Proc. of the 14th ACM SIGKDD conference, pages 426-434, 2008.
12. H. Li, Y. Wang, D. Zhang, M. Zhang, and E. Y. Chang. Pfp: parallel fp-growth for query recommendation. In Proc. of the 2008 ACM RecSys conference, pages 107-114, 2008.
13. A. McCallum, A. Corrada-Emmanuel, and X. Wang. The author-recipient-topic model for topic and role discovery in social networks: Experiments with enron and academic email. Technical report, Computer Science, University of Massachusetts Amherst, 2004.
14. J. J. Sandvig, B. Mobasher, and R. Burke. Robustness of collaborative recommendation based on association rule mining. In Proc. of the 2007 ACM Recommender Systems conference, pages 105-112, New York, NY, USA, 2007. ACM.
15. M.-L. Shyu, C. Haruechaiyasak, S.-C. Chen, and N. Zhao. Collaborative filtering by mining association rules from user access sequences. In Proc. of the International workshop on Challenges in WIRI, pages 128-135, 2005.
16. M. Snir and S. Otto. MPI-The Complete Reference: The MPI Core. MIT Press, 1998.
17. E. Spertus, M. Sahami, and O. Buyukkokten. Evaluating similarity measures: a large-scale study in the orkut social network. In Proc. of the 11th ACM SIGKDD Conference, pages 678-684, 2005.
18. R. Srikant and R. Agrawal. Mining generalized association rules. Future Gener. Comput. Syst., 13(2-3):161-180, 1997.
19. M. Steyvers, P. Smyth, M. Rosen-Zvi, and T. Griffiths. Probabilistic author-topic models for information discovery.In Proc. of the 10th ACM SIGKDD Conference, pages 306-315, 2004.
20. R. Thakur, R. Rabenseinfer, and W. Gropp. Optimization of collective communication operations in MPICH. International Journal of High Performance Computing Applications, 19(1):49-66, 2005.