Cold-start recommendation using Bi-clustering and fusion for large-scale social recommender systems

IEEE Transactions on Emerging Topics in Computing

Volumn 2, Issue 2, 2014, Pages 239-250

  Zhang, Daqiang ^a,b   Hsu, Ching Hsien ^c   Chen, Min ^d   Chen, Quan ^e   Xiong, Naixue ^f   Lloret, Jaime ^g  

^a TONGJI UNIVERSITY   (China)

^b NANJING NORMAL UNIVERSITY   (China)

^c CHUNG HUA UNIVERSITY   (Taiwan)

^d HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^e SHANGHAI JIAO TONG UNIVERSITY   (China)

^f Colorado Technical University ^*  (United States)

^g UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

Author keywords

Biclustering; Collaborative Filtering; Fusion; Keywords Cold start Problem; Smoothing

Indexed keywords

FUSION REACTIONS; RECOMMENDER SYSTEMS; SOCIAL NETWORKING (ONLINE);

BI-CLUSTERING; COLD START PROBLEMS; COLD-START RECOMMENDATIONS; DATA SPARSITY; FUSION TECHNIQUES; SMOOTHING; SOCIAL RECOMMENDER SYSTEMS; WIDE SPECTRUM;

COLLABORATIVE FILTERING;

EID: 84926519272     PISSN: None     EISSN: 21686750     Source Type: Journal    
DOI: 10.1109/TETC.2013.2283233     Document Type: Article

References (36)

1. X. Hu, T. H. S. Chu, H. C. B. Chan, and V. C. M. Leung, "Vita: A crowdsensing-oriented mobile cyber physical system," IEEE Trans. Emerg. Topics Comput., vol. 1, no. 1, pp. 148-165, Jun. 2013.
2. I. Guy and D. Carmel, "Social recommender systems," in Proc. 20th Int. Conf. World Wide Web, 2011, pp. 283-284.
3. D. Zhang, Q. Zou, and H. Xiong, "CRUC: Cold-start recommendations using collaborative filtering in internet of things," Energy Proc., vol. 13, pp. 3454-3461, Dec. 2011.
4. F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor, Recommender Systems Handbook. New York, NY, USA: Springer-Verlag, Oct. 2011.
5. J. Noel, S. Sanner, K.-N. Tran, P. Christen, L. Xie, E. V. Bonilla, E. Abbasnejad, and N. Della Penna, "New objective functions for social collaborative filtering," in Proc. 21st Int. Conf. World Wide Web, 2012, pp. 859-868.
6. G. Linden, B. Smith, and J. York, "Amazon. com recommendations: Itemto-item collaborative filtering, " IEEE Internet Comput., vol. 7, no. 1, pp. 76-80, Jan./Feb. 2003.
7. A. S. Das, M. Datar, A. Garg, and S. Rajaram, "Google news personalization: Scalable online collaborative filtering," in Proc. 16th Int. WWW Conf., 2007, pp. 271-280.
8. D. Zhang, J. Cao, M. Guo, J. Zhou, and R. Vaskar, "An efficient collaborative filtering approach using smoothing and fusing," in Proc. ICPP, 2009, pp. 147-154.
9. M. Khabbaz and L. V. S. Lakshmanan, "TopRecs: Top-k algorithms for item-based collaborative filtering," in Proc. EDBT, 2011, pp. 213-224.
10. N. Koenigstein, G. Dror, and Y. Koren, "Yahoo! music recommendations: Modeling music ratings with temporal dynamics and item taxonomy," in Proc. 5th ACM Conf. RecSys, 2011, pp. 165-172.
11. J. Noel, S. Sanner, K.-N. Tran, P. Christen, L. Xie, E. V. Bonilla, E. Abbasnejad, and N. Della Penna, "New objective functions for social collaborative filtering," in Proc. 21st Int. Conf. WWW, 2012, pp. 859-868.
12. B. Xu, J. Bu, C. Chen, and D. Cai, "An exploration of improving collaborative recommender systems via user-item subgroups," in Proc. 21st Int. Conf. WWW, Apr. 2012, pp. 21-30.
13. Z. Ma, S. Li, H. Luo, J. Guo, P. Gallinari, and D. Chen, "A cross-domain recommendation model for cyber-physical systems," IEEE Trans. Emerg. Topics Comput., to be published.
14. P. Victor, C. Cornelis, A. Teredesai, and M. De Cock, "Whom should I trust?: The impact of key figures on cold start recommendations," in Proc. ACM Symp. Appl. Comput., 2008, pp. 2014-2018.
15. K. Zhou, S.-H. Yang, and H. Zha, "Functional matrix factorizations for cold-start recommendation," in Proc. 34th Int. ACM SIGIR, 2011, pp. 315-324.
16. R M. Rodríguez, M. Espinilla, P. J. Sanchez, and L. M. Lopez, "Using linguistic incomplete preference relations to cold start recommendations," Internet Res., vol. 20, no. 3, pp. 296-315, 2010.
17. Y. Koren, "Factorization meets the neighborhood: A multifaceted collaborative filtering model," in Proc. 14th ACM SIGKDD, 2008, pp. 426-434.
18. H. J. Ahn, "A new similarity measure for collaborative filtering to alleviate the new user cold-starting problem," Inf. Sci., vol. 178, no. 1, pp. 37-51, 2008.
19. A. Schein, A. Popescul, L. Ungar, and D. Pennock, "Generative models for cold-start recommendations," in Proc. SIGIR Workshop, vol. 6. 2001, pp. 10-15.
20. W. Chu and S.-T. Park, "Personalized recommendation on dynamic content using predictive bilinear models," in Proc. 18th Int. Conf. WWW, 2009, pp. 691-700.
21. A. K. Menon, K. P. Chitrapura, S. Garg, D. Agarwal, and N. Kota, "Response prediction using collaborative filtering with hierarchies and side-information," in Proc. 17th ACM SIGKDD, 2011, pp. 141-149.
22. S. Park, D. Pennock, O. Madani, N. Good, and D. DeCoste, "Naïve filterbots for robust cold-start recommendations," in Proc. 12th ACM SIGKDD, 2006, pp. 705-712.
23. T. George and S. Merugu, "A scalable collaborative filtering framework based on co-clustering," in Proc. 5th IEEE ICDM, Nov. 2005, pp. 625-628.
24. M. Deodhar and J. Ghosh, "A framework for simultaneous co-clustering and learning from complex data," in Proc. 13th ACM SIGKDD, 2007, pp. 250-259.
25. G. Chen, F. Wang, and C. Zhang, "Collaborative filtering using orthogonal nonnegative matrix tri-factorization," Inf. Process. Manag., vol. 45, no. 3, pp. 368-379, 2009.
26. K. W.-T. Leung, D. L. Lee, and W.-C. Lee, "CLR: A collaborative location recommendation framework based on co-clustering," in Proc. 34th Int. ACM SIGIR Conf., 2011, pp. 305-314.
27. M. Armbrust, A. Fox, R. Grifth, A. D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, "A view of cloud computing," Commun. ACM, vol. 53, no. 4, pp. 50-58, 2010.
28. S. Lee, D. Lee, and S. Lee, "Personalized DTV program recommendation system under a cloud computing environment," IEEE Trans. Consumer Electron., vol. 56, no. 2, pp. 1034-1042, May 2010.
29. C.-F. Lai, J.-H. Chang, C.-C. Hu, Y.-M. Huang, and H.-C. Chao, "CPRS: A cloud-based program recommendation system for digital TV platforms," Future Generat. Comput. Syst., vol. 27, no. 6, pp. 823-835, 2011.
30. J. Jiang, W. Pang, Y. Deng, K. He, and Z. Gu, "A blog personality recommender system based on cloud computing infrastructure," in Proc. IJCSS, May 2012, pp. 1-5.
31. Y. Zhou, Y. Zhang, H. Liu, N. Xiong, and A. V. Vasilakos, "A baremetal and asymmetric partitioning approach to client virtualization," IEEE Trans. Services Comput., to be published.
32. 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.
33. G. Xue, C. Lin, Q. Yang, W. Xi, H. Zeng, Y. Yu, and Z. Chen, "Scalable collaborative filtering using cluster-based smoothing," in Proc. 28th Annu. Int. ACM SIGIR Conf., 2005, pp. 114-121.
34. H. Ma, I. King, and M. R. Lyu, "Effective missing data prediction for collaborative filtering," in Proc. 30th Annu. Int. ACM SIGIR Conf., 2007, pp. 39-46.
35. I. S. Dhillon, S. Mallela, and D. S. Modha, "Information-theoretic co-clustering," in Proc. 9th ACM SIGKDD Int. Conf. KDD, 2003, pp. 89-98.
36. K. W.-T. Leung, D. L. Lee, and W.-C. Lee, "CLR: A collaborative location recommendation framework based on co-clustering," in Proc. 34th Int. ACM SIGIR Conf., 2011, pp. 305-314.