Svm and Collaborative filtering-based prediction of user preference for digital fashion recommendation systems

IEICE Transactions on Information and Systems

Volumn E90-D, Issue 12, 2007, Pages 2100-2103

  Kang, Hanhoon ^a   Yoo, Seong Joon ^a  

^a Sejong University   (South Korea)

Author keywords

Machine Learning; Personalized search; Recommendation

Indexed keywords

ARTIFICIAL INTELLIGENCE; FORECASTING; LEARNING SYSTEMS;

MACHINE LEARNING TECHNIQUES; MISSING VALUES; ONLINE SHOPPING; PERSONALIZED SEARCH; RECOMMENDATION; SUPPORT VECTOR REGRESSION (SVR); UNIQUE FEATURES; USER HISTORY;

COLLABORATIVE FILTERING;

EID: 68249135550     PISSN: 09168532     EISSN: 17451361     Source Type: Journal    
DOI: 10.1093/ietisy/e90-d.12.2100     Document Type: Article

References (10)

1. S.-S. Weng and M.-J. Liu, "Personalized product recommendation in e-commerce," IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04), pp. 413-420, 2004.
2. J.A. Xu and K. Araki, "A personalized recommendation system for electronic program guide," AI 2005, LNCS 3809, pp. 1146-1149, 2005.
3. D. Billsus and M.J. Pazzani, "Learning collaborative information filters," ICML 1998, pp. 46-54, 1998.
4. Collaborative Filtering, http://en.wikipedia.org/wiki/
5. M. Balabanovic and Y. Shoham, "Fab: Content-based collaborative recommendation," Commun. ACM, vol. 40, no. 3, pp. 66-72, 1997.
6. M.W. Berry, "Large scale sparse singular value computations," Int.J. Supercomput. Appl., vol. 6, no. 1, pp. 13-49, 1992.
7. M.H. Law and J.T. Kwok, "Bayesian support vector regression," Proc. 8th International Workshop on AISTATS 2001, pp. 239-244, 2001.
8. MovieLens, http://www.grouplens.org/node/12#attachment
9. R.A. Calvo and H.A. Ceccatto, "Intelligent document classification," Intell. Data Anal., vol. 4, no. 5, pp. 411-420, 2000.
10. S. Gerard, Introduction to Modern Information Retrieval, McGraw-Hill, 1983.