1 |
S. H. Jo, "Weight recommendation technique based on item quality to improve performance of new user recommendation and recommendation on the web," Ph.D. dissertation, Hannam University, Daejeon, Korea, 2008.
|
2 |
S. J. Lee, T. R. Jeon, G. D, Baek, and S. S. Kim, "A movie rating prediction system of user propensity analysis based on collaborative filtering and fuzzy system," Journal of Korean Institute of Intelligent Systems, vol. 19, no. 2, pp. 242-247, 2009.
DOI
|
3 |
H. C. Lee, S. J. Lee, and S. O. Kim, "A study on improvements of prediction accuracy using additional information in collaborative filtering," in Proceedings of the Korean Accounting Association 2009 Spring Conference, Seoul, Korea, 2009, pp. 349-352.
|
4 |
G. Lekakos and G. M. Giaglis, "Improving the prediction accuracy of recommendation algorithms: approaches anchored on human factors," Interacting with Computers, vol. 18, no. 3, pp. 410-431, 2006.
DOI
|
5 |
K. R. Kim, J. H. Byeon, and N. M. Moon, "Collaborative filtering design using genre similarity and preffered genre," Journal of the Korea society of Computer and Information, vol. 16, no. 4, pp. 159-168, 2011.
DOI
|
6 |
H. Ma, I. King, and M. R. Lyu, "Effective missing data prediction for collaborative filtering," in Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Amsterdam, The Netherlands, 2007, pp. 39-46.
|
7 |
P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl, "GroupLens: an open architecture for collaborative filtering of netnews," in Proceeding of the 1994 ACM Conference on Computer Supported Cooperative Work, Chapel Hill, NC, 1994, pp. 175-186.
|
8 |
J. Wang, A. P. de Vries, and M. J. Reinders, "Unifying user-based and item-based collaborative filtering approaches by similarity fusion," in Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Seattle, WA, 2006, pp. 501-508.
|
9 |
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 Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Salvador, Brazil, 2005, pp. 114-121.
|
10 |
T. Hofmann, "Latent semantic models for collaborative filtering," ACM Transactions on Information Systems, vol. 22, no. 1, pp. 89-115, 2004.
DOI
|
11 |
GroupLens, "MovieLens datasets," [Online]. Available: http://www.grouplens.org/node/73.
|
12 |
D. M. Pennock, E. Horvitz, S. Lawrence, and C. L. Giles, "Collaborative filtering by personality diagnosis: a hybrid memory- and model-based approach," in Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence, Stanford, CA, 2000, pp. 473-480.
|
13 |
J. S. Breese, D. Heckerman, and C. Kadie, "Empirical analysis of predictive algorithms for collaborative filtering," in Proceedings of the 14th conference on Uncertainty in Artificial Intelligence, Madison, WI, 1998, pp. 43-52.
|
14 |
D. S. Park, "Improved movie recommendation system based-on personal propensity and collaborative filtering," KIPS Transactions of Computer and Communication System, vol. 2, no. 11, pp. 475-482, 2013.
DOI
|
15 |
S. C, Oh and M. Choi, "Effective combination of user-based and item-based methods for movie recommendation," in Proceedings of the 2013 Korean Society of Internet Information (KSII) Fall Conference, Seoul, Korea, 2013, pp. 135-136.
|