Lazy collaborative filtering for data sets with missing values

IEEE Transactions on Cybernetics

Volumn 43, Issue 6, 2013, Pages 1822-1834

  Ren, Yongli ^a   Li, Gang ^a   Zhang, Jun ^a   Zhou, Wanlei ^a  

^a DEAKIN UNIVERSITY   (Australia)

Author keywords

Imputation; Neighborhood based collaborative filtering (CF); Recommender systems

Indexed keywords

DATA SPARSITY; HISTORICAL INFORMATION; IMPUTATION; IMPUTATION METHODS; MISSING VALUES; NEIGHBORHOOD-BASED COLLABORATIVE FILTERING (CF); RECOMMENDATION METHODS;

RECOMMENDER SYSTEMS;

COLLABORATIVE FILTERING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; DATA MINING; FACTUAL DATABASE; INFORMATION RETRIEVAL; METHODOLOGY; SAMPLE SIZE; SIGNAL PROCESSING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DATA MINING; DATABASES, FACTUAL; INFORMATION STORAGE AND RETRIEVAL; PATTERN RECOGNITION, AUTOMATED; SAMPLE SIZE; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84890016550     PISSN: 21682267     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2012.2231411     Document Type: Article

References (34)

1. G. Adomavicius and A. Tuzhilin, "Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions," IEEE Trans. Knowl. Data Eng., vol. 17, no. 6, pp. 734-749, Jun. 2005. (Pubitemid 40860454)
2. C. Desrosiers and G. Karypis, "A comprehensive survey of neighborhoodbased recommendation methods," in Recommender Systems Handbook, F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor, Eds. New York: Springer-Verlag, 2011, ch. 4, pp. 107-144.
3. R.M. Bell and Y. Koren, "Lessons from the Netflix prize challenge," ACM SIGKDD Expl. Newslett., vol. 9, no. 2, pp. 75-79, Dec. 2007.
4. P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl, "GroupLens: An open architecture for collaborative filtering of netnews," in Proc. ACM Conf. Comput. Supported Coop. Work, 1994, pp. 175-186.
5. J. Breese, D. Heckerman, and C. Kadie, "Empirical analysis of predictive algorithms for collaborative filtering," in Proc. 14th Conf. Uncertainty Artif. Intell., 1998, pp. 43-52.
6. L. M. D. Campos, J. M. Fernández-luna, J. F. Huete, and M. A. Rueda-morales, "Measuring predictive capability in collaborative filtering," in Proc. 3rd ACM Conf. Recommender Syst., 2009, pp. 313-316.
7. M. Larson and A. Hanjalic, "Exploiting user similarity based on rateditem pools for improved user-based collaborative filtering," in Proc. 3rd ACM Conf. Recommender Syst., 2009, pp. 125-132.
8. G.-R. Xue, C. Lin, Q. Yang, W. Xi, H.-J. Zeng, Y. Yu, and Z. Chen, "Scalable collaborative filtering using cluster-based smoothing," in Proc. SIGIR, 2005, pp. 114-121.
9. H. Ma, I. King, and M. R. Lyu, "Effective missing data prediction for collaborative filtering," in Proc. SIGIR, 2007, pp. 39-46. (Pubitemid 350164942)
10. X. Su, T. M. Khoshgoftaar, and R. Greiner, "A mixture imputationboosted collaborative filter," in Proc. FLAIRS Conf., 2008, pp. 312-316.
11. X. Zhu, S. Zhang, Z. Jin, Z. Zhang, and Z. Xu, "Missing value estimation for mixed-attribute data sets," IEEE Trans. Knowl. Data Eng., vol. 23, no. 1, pp. 110-121, Jan. 2011.
12. S. Zhang, Z. Jin, and X. Zhu, "Missing data imputation by utilizing information within incomplete instances," J. Syst. Softw., vol. 84, no. 3, pp. 452-459, Mar. 2011.
13. S. Zhang, "Shell-neighbor method and its application in missing data imputation," Appl. Intell., vol. 35, no. 1, pp. 123-133, Aug. 2011.
14. T. Cover, "Estimation by the nearest neighbor rule," IEEE Trans. Inf. Theory, vol. IT-14, no. 1, pp. 50-55, Jan. 1968.
15. B. Sarwar, G. Karypis, J. Konstan, and J. Reidl, "Item-based collaborative filtering recommendation algorithms," in Proc. 10th Int. Conf.WorldWide Web, 2001, pp. 285-295.
16. S. A. Goldman and M. K. Warmuth, "Learning binary relations using weighted majority voting," Mach. Learn., vol. 20, no. 3, pp. 245-271, Sep. 1995.
17. R. M. Bell and Y. Koren, "Improved neighborhood-based collaborative filtering," in Proc. KDD-Cup Workshop 13th Int. Conf. ACM SIGKDD, 2007, pp. 7-14.
18. F. Garcin, B. Faltings, R. Jurca, and N. Joswig, "Rating aggregation in collaborative filtering systems," in Proc. 3rd ACM Conf. Recommender Syst., 2009, pp. 349-352.
19. A. Nakamura and N. Abe, "Collaborative filtering using weighted majority prediction algorithms," in Proc. Int. Conf. Mach. Learn., 1998, pp. 395-403.
20. X. Su and T. Khoshgoftaar, "Collaborative filtering for multi-class data using belief nets algorithms," in Proc. IEEE 18th ICTAI, Nov. 2006, pp. 497-504. (Pubitemid 351209558)
21. B. Sarwar, G. Karypis, and J. Konstan, "Recommender systems for largescale e-commerce: Scalable neighborhood formation using clustering," in Proc. 5th Int. Conf. Comput. Inf. Technol., 2002, pp. 1-6.
22. T. Hofmann and J. Puzicha, "Latent class models for collaborative filtering," in Proc. Int. Joint Conf. Artif. Intell., 1999, vol. 16, pp. 688-693.
23. D. Lemire and A. Maclachlan, "Slope one predictors for online ratingbased collaborative filtering," in Proc. SDM, 2005, pp. 1-5.
24. D. Billsus andM. Pazzani, "Learning collaborative information filters," in Proc. 15th Int. Conf. Mach. Learn., 1998, pp. 46-54.
25. Y. Koren, "Factorization meets the neighborhood: A multifaceted collaborative filtering model," in Proc. SIGKDD, 2008, pp. 426-434.
26. R. Bell, Y. Koren, and C. Volinsky, "Modeling relationships at multiple scales to improve accuracy of large recommender systems," in Proc. 13th Int. Conf. ACM SIGKDD Mining, 2007, pp. 95-104.
27. M. R. Mclaughlin and J. L. Herlocker, "A collaborative filtering algorithm and evaluation metric that accurately model the user experience," in Proc. SIGIR, 2004, pp. 329-336.
28. C. Desrosiers and G. Karypis, "A novel approach to compute similarities and its application to item recommendation," in Proc. PRICAI, 2010, pp. 39-51.
29. S. Chee, J. Han, and K. Wang, "Rectree: An efficient collaborative filtering method," in Proc. Data Warehousing Knowl. Discovery, 2001, pp. 141-151. (Pubitemid 33332762)
30. R. Johnson and G. K. Bhattacharyya, Statistics: Principles and Methods, 6th ed. Hoboken, NJ: Wiley, 2009.
31. N. S. Altman, "An introduction to Kernel and nearest-neighbor nonparametric regression," Amer. Stat., vol. 46, no. 3, pp. 175-181, Aug. 1992.
32. X. Su and T. M. Khoshgoftaar, "A survey of collaborative filtering techniques," Adv. Artif. Intell., vol. 2009, pp. 421425-1-421425-19, Jan. 2009.
33. J. Zhang, Y. Xiang, Y. Wang, W. Zhou, Y. Xiang, and Y. Guan, "Network traffic classification using correlation information," IEEE Trans. Parallel Distrib. Syst., vol. 24, no. 1, pp. 104-117, Jan. 2013.
34. J. Wang, A. P. de Vries, and M. J. T. Reinders, "Unifying user-based and item-based collaborative filtering approaches by similarity fusion," in Proc. SIGIR, 2006, pp. 501-508.