基于集团序推荐输出的协同过滤推荐算法

石丽丽; 刘茜领; 张国东

doi:10.3969/j.issn.1004-1478.2012.02.020

March 2012

Article Contents

SHI Li-li, LIU Qian-ling and ZHANG Guo-dong. Collaborative filtering recommendation algorithm based on aggregative rank recommendation output[J]. Journal of Light Industry, 2012, 27(2): 80-83. doi: 10.3969/j.issn.1004-1478.2012.02.020

Citation: SHI Li-li, LIU Qian-ling and ZHANG Guo-dong. Collaborative filtering recommendation algorithm based on aggregative rank recommendation output[J]. Journal of Light Industry, 2012, 27(2): 80-83. doi: 10.3969/j.issn.1004-1478.2012.02.020 shu

Collaborative filtering recommendation algorithm based on aggregative rank recommendation output

School of Comp. and Infor. Eng., He'nan Univ., Kaifeng 475004, China

Received Date: 2011-12-21
Available Online: 2012-03-15

Abstract

Aiming at the problem that traditional item similarity of e-commerce recommedation system has shortage in calculation and the recommedation output of TOP-N lacks personalization,an improvement algorithm was put forword.This algorithm calculates item similarity using dynamic weigh factor method,classifies items using fuzzy clustering,introduces user weigh factor in forecasting evaluation formula and carries out recommendation output to confirm candidate N value.The experimental results showed that this algorithm not only solved the problem of sparse data and improved the recommendation quality and enhanced the recommendation personalized degree.
- collaborative filtering recommendation algorithm,
- fuzzy clustering,
- aggregative rank,
- item similarity calculation
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沈阳化工大学材料科学与工程学院沈阳 110142

Collaborative filtering recommendation algorithm based on aggregative rank recommendation output

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通讯作者: 陈斌, bchen63@163.com