Research of Data Sparsity Based on Collaborative Filtering Algorithm

Li Min Liu; Peng Xiang Zhang; Le Lin; Zhi Wei Xu

doi:10.4028/www.scientific.net/AMM.462-463.856

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 462-463Research of Data Sparsity Based on Collaborative...

Research of Data Sparsity Based on Collaborative Filtering Algorithm

Abstract:

During the traditional collaborative filtering recommendation algorithm be impacted by itself data sparseness problem. It can not provide accurate recommendation result. In this paper, Using traditional collaborative filtering algorithm and the concept of similar level, take advantage of the idea of data populating to solve sparsity problem, then using the Weighted Slope One algorithm to recommend calculating. Experimental results show that the improved algorithm solved the problem of the recommendation results of low accuracy because of the sparse scoring matrix, and it improved the algorithm recommended results to a certain extent.

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Periodical:

Applied Mechanics and Materials (Volumes 462-463)

Pages:

856-860

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.462-463.856

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Online since:

November 2013

Authors:

Li Min Liu, Peng Xiang Zhang*, Le Lin, Zhi Wei Xu

Keywords:

Collaborative Filtering (CF), Data Sparsity, E-Commerce, Personalized Recommendation

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* - Corresponding Author

References

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