The week's pick
Reseach Article
An Efficient Approach Based on Trust to Purge the Weakness of Recommendation System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 25 |
| Year of Publication: 2010 |
| Authors: M.K. Kavitha Devi, P. Venkatesh, N. Benasirsiddiqa, R.Archana |
10.5120/464-769
|
M.K. Kavitha Devi, P. Venkatesh, N. Benasirsiddiqa, R.Archana . An Efficient Approach Based on Trust to Purge the Weakness of Recommendation System. International Journal of Computer Applications. 1, 25 ( February 2010), 13-21. DOI=10.5120/464-769
Abstract
Recommendations are the need of the hour in e-commerce sector. It allows user’s to shop according to their desire. Finding similarity between users to recommend items is the common concept used in most of the collaborative recommendation system. However there are many problems like sparsity, recommending items to cold-start user and handling copy-profile attack(Shilling’s attack).To overcome these setbacks we make use of trust and distrust statements and propose a novel method to increase the accuracy of recommended items.
References
- 1. Sizwe M. Dhlamini, Tshilidzi Marwala, “An application of SVM, RBF and MLP with ARD on Bushings”, Proceedings of the 2004 IEEE conference on Cybernetics and Intelligence Systems.
- 2. Anna Goy, Liliana Ardissono, and Giovanna Petrone, “Personalization in E-commerce Applications”, the adaptive web, springer-verlag Berlin Heidelberg LNCS 4321, pp.485-520, 2007.
- 3. Resinck 97, P.Resnick and H.Varian.Recommender Systems. In communication of the ACM, Pages 56-58, 1997.
- 4. Using Trust in Recommender Systems: an Experimental Analysis .Paolo Massa, Bobby Bhattacharjee
- 5. Gediminas Adomavicius, and Alexander Tuzhilin, “Towards the Next Generation of Recommender Systems: A Survey of the state-of-the-Art and Possible Extensions”, IEEE Transactions on Knowledge and Data Engineering, Vol. 17, No.6, June 2005.
- 6. Kwok-Wai Cheung, Kwok-Ching Tsui, and Jiming Liu, “Extended Latent class Models for Collaborative Recommendation”, IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, Vol.34, No. 1, January 2004.
- 7. Trust metrics on controversial users: balancing between tyranny of the majority and echo Chambers, 2007. Paolo Massa, Paolo Avesani.
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