A Collaborative Filtering Recommendation Algorithm Combined with User and Item

Feng Ming Liu; Hai Xia Li; Peng Dong

doi:10.4028/www.scientific.net/AMM.513-517.1878

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517A Collaborative Filtering Recommendation Algorithm...

A Collaborative Filtering Recommendation Algorithm Combined with User and Item

Abstract:

The collaborative filtering recommendation algorithm based on user is becoming the more personalized recommendation algorithm. But when the user evaluation for goods is very small and the user didnt evaluate the item, the commodity recommendation based on the item evaluation of user may not be accurate, and this is the sparseness in the collaborative filtering algorithm based on user. In order to solve this problem, this paper presents a collaborative filtering recommendation algorithm based on user and item. The experimental results show that this method has smaller MAE and greatly improve the quality of the recommendation in the recommendation system.

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Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

1878-1881

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.1878

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Cite this paper

Online since:

February 2014

Authors:

Feng Ming Liu*, Hai Xia Li, Peng Dong

Keywords:

Collaborative Filtering (CF), ITEM, Recommendation Algorithm, Sparseness, User

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* - Corresponding Author

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