HYREC: a hybrid recommendation system for e-commerce

被引:0
|
作者
Prasad, B [1 ]
机构
[1] Florida A&M Univ, Dept Informat & Comp Sci, Tallahassee, FL 32307 USA
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暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Product recommendation is very important in business to customer (B2C) e-commerce. Automated Collaborative Filtering (ACF) is an important approach for product recommendation. However, a major drawback with this approach is that it can't avoid the "sequence recognition problem", explained in this paper. Here we present a system that addresses the sequence recognition problem by recording and utilizing the users' purchase patterns and ratings. The proposed system is a fruitful combination of ACF and Case-Based Reasoning Plan Recognition (CBRPR) methods. The evaluation studies prove that the hybrid system provides better performance when compared to ACF and CBRPR methods used individually.
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页码:408 / 420
页数:13
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