Research on Automatic Recommender System Based on Data Mining

被引：0

作者：

Chen, Qingzhang ^{[1
]}

Chen, Qiaoyan ^{[1
]}

Wang, Kai ^{[1
]}

Tang, Zhongzhe ^{[1
]}

Pei, Yujie ^{[1
]}

机构：

[1] Zhejiang Univ Technol, Dept Comp Sci & Technol, Hangzhou 310000, Zhejiang, Peoples R China

来源：

EMERGING RESEARCH IN WEB INFORMATION SYSTEMS AND MINING | 2011年 / 238卷

关键词：

the automatic recommender system; Adaptive Resonance Theory; data mining technology; association rules;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

By using ART neural network and data mining technology, this study builds a typical online recommendation system. It can automatically cluster population characteristics and dig out the associated characteristics. Aiming at the characteristics of recommendation system and users' attribute weights, this paper propose a modified ART algorithm for clustering MART algorithm. It makes recommendation system to set the weight value of each attribute node based on the importance of user attributes. The experiment shows that the MART algorithm has better performance than the conventional ART algorithm and can get more reasonable and flexible clustering results.

引用

页码：28 / 35

页数：8

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