An Improved Collaborative Filtering Recommendation Algorithm

被引：0

作者：

Wan, Li-Yong ^{[1
]}

Xia, Lei ^{[2
]}

机构：

[1] Nanchang Inst Sci & Technol, Sch Elect & Informat Engn, Nanchang 330108, Peoples R China

[2] Nanchang Inst Sci & Technol, Informat Technol & Training Ctr, Nanchang 330108, Peoples R China

来源：

PROCEEDINGS OF THE 2016 6TH INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS, ENVIRONMENT, BIOTECHNOLOGY AND COMPUTER (MMEBC) | 2016年 / 88卷

关键词：

Collaborative Filtering; Recommendation; CLIQUE; Recommended Efficiency;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

With the inflationary development of data sizes, the traditional recommendation system the recommendation efficiency of the recommendation system encounters a great challenge. This paper proposes an improved collaborative filtering algorithm. The algorithm firstly implements the clustering operation data, takes average rating and evaluated times of item as dimension of two dimensional grids, and then implements clustering based on item with CLIQUE grid clustering algorithm in accordance with item similarity. The corresponding experiment shows the method can significantly improve the recommendation efficiency of the recommendation system.

引用

页码：1354 / 1357

页数：4