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- W2384342389 abstract "This paper presents a novel hybrid recommender system for e-commerce.The following three phases are approached,clustering the customers and the products with an improved K-means algorithm, analyzing the association rules on transaction history using the logistic regression,and integrating all rules in a linear information fusion model,to achieve a valuable recommendation result.The implementation on a practical business application of this system is also introduced in this paper.The performance evaluation validates the recommendation result,and proves that our system works better in the sort of vertical e-commerce websites with higher prediction accuracy." @default.
- W2384342389 created "2016-06-24" @default.
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- W2384342389 date "2010-01-01" @default.
- W2384342389 modified "2023-09-25" @default.
- W2384342389 title "Hybrid recommender system for vertical e-commerce website" @default.
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