Discrete collaborative filtering

SIGIR 2016 - Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2016, Pages 325-334

  Zhang, Hanwang ^a   Shen, Fumin ^b   Liu, Wei ^c   He, Xiangnan ^a   Luan, Huanbo ^d   Chua, Tat Seng ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^c Didi Research   (China)

^d TSINGHUA UNIVERSITY   (China)

Author keywords

Collaborative Filtering; Discrete hashing; Recommendation

Indexed keywords

ALGORITHMS; BINARY CODES; BINS; CODES (SYMBOLS); INFORMATION RETRIEVAL; OPTIMIZATION; VECTOR SPACES;

BINARY QUANTIZATION; COMPUTATIONALLY EFFICIENT; DISCRETE CONSTRAINTS; DISCRETE HASHING; DISCRETE OPTIMIZATION; HASHING TECHNIQUES; LEARNING PROCEDURES; RECOMMENDATION;

COLLABORATIVE FILTERING;

EID: 84980322368     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2911451.2911502     Document Type: Conference Paper

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. TKDE, 2005.
2. D. Agarwal, B.-C. Chen, and P. Elango. Fast online learning through offline initialization for time-sensitive recommendation. In KDD, 2010.
3. S. Balakrishnan and S. Chopra. Collaborative ranking. In WSDM, 2012.
4. J. Bennett and S. Lanning. The netflix prize. In KDD, 2007.
5. J. Bobadilla, F. Ortega, A. Hernando, and A. Gutiérrez. Recommender systems survey. Knowledge-Based Systems, 2013.
6. A. S. Das, M. Datar, A. Garg, and S. Rajaram. Google news personalization: scalable online collaborative filtering. In WWW, 2007.
7. A. Gionis, P. Indyk, R. Motwani, et al. Similarity search in high dimensions via hashing. In VLDB, 1999.
8. K. Goldberg, T. Roeder, D. Gupta, and C. Perkins. Eigentaste: A constant time collaborative filtering algorithm. Information Retrieval, 2001.
9. Y. Gong, S. Lazebnik, A. Gordo, and F. Perronnin. Iterative quantization: A procrustean approach to learning binary codes for large-scale image retrieval. TPAMI, 2013.
10. E. F. Harrington. Online ranking/collaborative filtering using the perceptron algorithm. In ICML, 2003.
11. J. Håstad. Some optimal inapproximability results. JACM, 2001.
12. X. He, T. Chen, M.-Y. Kan, and X. Chen. Trirank: Review-aware explainable recommendation by modeling aspects. In CIKM, 2015.
13. X. H. He, H. Zhang, M.-Y. Kan, and T.-S. Chua. Fast matrix factorization for online recommendation with implicit feedback. In SIGIR, 2016.
14. A. Karatzoglou, M. Weimer, and A. J. Smola. Collaborative filtering on a budget. In AISTAT, 2010.
15. Y. Koren. Collaborative filtering with temporal dynamics. In KDD, 2009.
16. Y. Koren, R. Bell, and C. Volinsky. Matrix factorization techniques for recommender systems. Computer, 2009.
17. W. Liu, C. Mu, S. Kumar, and S.-F. Chang. Discrete graph hashing. In NIPS, 2014.
18. X. Liu, J. He, C. Deng, and B. Lang. Collaborative hashing. In CVPR, 2014.
19. H. Ma, D. Zhou, C. Liu, M. R. Lyu, and I. King. Recommender systems with social regularization. In WSDM, 2011.
20. J. Mairal, F. Bach, J. Ponce, and G. Sapiro. Online learning for matrix factorization and sparse coding. JMLR, 2010.
21. J. McAuley and J. Leskovec. Hidden factors and hidden topics: Understanding rating dimensions with review text. In RecSys, 2013.
22. M. Norouzi, A. Punjani, and D. J. Fleet. Fast search in hamming space with multi-index hashing. In CVPR, 2012.
23. S. Rendle. Scaling factorization machines to relational data. VLDB, 2013.
24. S. Rendle, C. Freudenthaler, Z. Gantner, and L. Schmidt-Thieme. Bpr: Bayesian personalized ranking from implicit feedback. In UAI, 2009.
25. B. Sarwar, G. Karypis, J. Konstan, and J. Riedl. Item-based collaborative filtering recommendation algorithms. In WWW, 2001.
26. F. Shen, C. Shen, W. Liu, and H. T. Shen. Supervised discrete hashing. In CVPR, 2015.
27. M. Volkovs and G. W. Yu. Effective latent models for binary feedback in recommender systems. In SIGIR, 2015.
28. J. Wang, S. Kumar, and S.-F. Chang. Semi-supervised hashing for large-scale search. TPAMI, 2012.
29. J. Wang, W. Liu, S. Kumar, and S.-F. Chang. Learning to hash for indexing big data: A survey. Proceedings of the IEEE, 2016.
30. M. Weimer, A. Karatzoglou, Q. V. Le, and A. Smola. Maximum margin matrix factorization for collaborative ranking. NIPS, 2007.
31. Y. Weiss, A. Torralba, and R. Fergus. Spectral hashing. In NIPS, 2009.
32. Z. Zhang, Q. Wang, L. Ruan, and L. Si. Preference preserving hashing for efficient recommendation. In SIGIR, 2014.
33. K. Zhou and H. Zha. Learning binary codes for collaborative filtering. In KDD, 2012.
34. Y. Zhou, D. Wilkinson, R. Schreiber, and R. Pan. Large-scale parallel collaborative filtering for the netflix prize. In AAIM, 2008.