An Improved Personalized Recommendation System Research

Xing Yuan Li; Qing Shui  Li

doi:10.4028/www.scientific.net/AMR.756-759.1398

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 756-759An Improved Personalized Recommendation System...

An Improved Personalized Recommendation System Research

Abstract:

In order to find information of interest and found valuable information resources in enrich Internet data. This paper describes a personalized recommendation system, personalized recommendation system is an intelligent recommendation system to help e-commerce site for customers to provide complete personalized shopping decision support and information services. for the User Rating data extreme sparseness, This paper presents nearest neighbor collaborative filtering algorithm based on project score predicted ,experiments show that this method can improve the quality of recommendation system.

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Periodical:

Advanced Materials Research (Volumes 756-759)

Pages:

1398-1402

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.756-759.1398

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Online since:

September 2013

Authors:

Xing Yuan Li, Qing Shui Li

Keywords:

Association Rule, Collaborative Filtering Recommendation, Personalized Recommendation, Project Score, Styling

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References

[1] Zhao Liang, Hu naiJing, Zhang Shouzhi, Personalized recommendation algorithm design, Computer Research and Development, Vo1. 39, No. 8 Aug. (2002).

Google Scholar

[2] Breese J, Hecherman D, Kadie C, Empirical analysis of predictive algorithms for collaborative filtering, " In: Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (UAI, 98). 1998. 43~52.

Google Scholar

[3] He An, Collaborative filtering in e- E-commerce recommendation systems research, Zhejiang: ZhejiangSchool of Computer Science, (2007).

Google Scholar

[4] Deng Ailin Zhu Yang Yong, Shi Bole, based on the project rating collaborative filtering prediction algorithm,. Software, 2003, 14(9) : 1621-1628.

Google Scholar

[5] Lu Lina, Yang Yiling, and Guan Xudong, the study of Web log mining in data preprocessing , Computer Engineering, 2000, 26 (4): pp.66-72.

Google Scholar

[6] Shi Jing, Gong Zhenyu, personalized service system based on Web usage mining, University of Electronic Science and Technology, 2002. 31 (4).

Google Scholar