Collaborative filtering system based on classification and extended K-means algorithm

Advances in Information Sciences and Service Sciences

Volumn 3, Issue 7, 2011, Pages 187-194

  Wu, Y K ^a   Tang, Z H ^a  

^a ZHEJIANG UNIVERSITY OF FINANCE AND ECONOMICS   (China)

Author keywords

Classification; Clustering; Collaborative filtering (CF); K means; Similarity

Indexed keywords

CATEGORY SYSTEMS; CLUSTERING; COLLABORATIVE FILTERING; COLLABORATIVE FILTERING (CF); COLLABORATIVE FILTERING SYSTEMS; COMPUTATIONAL SPEED; HARMFUL EFFECTS; ITEM CATEGORY; ITEM-BASED CF; K-MEANS; K-MEANS ALGORITHM; LARGE-SCALE PROBLEM; MATRIX; SIMILARITY;

FORECASTING;

CLUSTERING ALGORITHMS;

EID: 80052599588     PISSN: 19763700     EISSN: None     Source Type: Journal    
DOI: 10.4156/aiss.vol3.issue7.22     Document Type: Article

References (13)

1. Goldberg D, Nichols D, Oki B.M., Terry D, Using collaborative filtering to weave information tapestry, Communications of the ACM, vol. 3, no. 12, pp.61-70, 1992.
2. Konstan JA, Miller BN, Maltz D, GroupLens: Apply in collaborative filtering to usenet news, Comm ACM, vol. 40, no. 3, pp. 77-87, 1997.
3. Shardanand U, Maes P, Social information filtering: Algorithms for automating 'Word of Mouth', Proc Conf Human Factors in Computing Systems Denver, pp. 210-217, 1995.
4. Qiang Guo, Caiming Zhang, Image Interpolation using Collaborative Filtering, JDCTA: International Journal of Digital Content Technology and its Applications, Vol. 5, No. 4, pp. 12-17, 2011.
5. Btwese J, Heckemn D, Kadie C, Empirical analysis of predictive algorithms for collaborative filtering, In Proceedings of the 14Conference Oil Uncertainty in Artificial Intelligence, pp. 43-52, 1998.
6. Schein A I, Popescul A, Unger L H, Pennock D M, Methods and Metrics for cold-start recommendations, Proceeding of the 25th Annual International ACM SIGIR conference on Research, pp. 46-52, 2005.
7. Chen YL, Cheng LC, A novel collaborative filtering approach for recommending ranked items, Expert Systems with Applications, vol. 34, no. 4, pp. 2396-2405, 2008.
8. Zhang H P, Li H B, Li X, Collaborative Filtering Recommendation Algorithm Based on Item-class Rating, Journal of the China Society for Scientific and Technical Information, vol. 27, no. 2, pp. 218-223, 2008.
9. Dempster A, Laird N, Rubin D, Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society, vol. 39, no. 1,pp. 1-38, 1997.
10. Sarwar B, Karypis G, Konstan J, Item-based collaborative filtering recommendation algorithms, Proc 10th Int'1 WWW Conf, Hong Kong, pp. 1-5, 2001.
11. Yang MH, Gu ZM, Personalized recommendation based on partial similarity of interests, Advanced Data Mining and Applications Proceedings, pp. 509-516, 2006.
12. Liu J G, Zhou T, Wang B H, Research Progress on Recommendation System, Progress in Natural Science, vol. 19, no.1, pp. 1-15, 2009.
13. Chein-Shung Hwang, Genetic Algorithms for Feature Weighting in Multi-criteria Recommender Systems, JCIT: Journal of Convergence Information Technology, Vol. 5, No. 8, pp. 126-136, 2010.