Study of the Model of E-commerce Personalized Recommendation System Based on Data Mining

As the current personalized recommendation systems of Internet bookstore are limited too much in function, this paper build a kind of Internet bookstore recommendation system based on “Strategic Data Mining”, which can provide personalized recommendations that they really want. It helps us to get the weight attribute of type of book by using AHP, the weight attributes spoken on behalf of its owner, and we add it in association rules. Then the method clusters the customer and type of book, and gives some strategies of personalized recommendation. Internet bookstore recommendation system is implemented with ASP.NET in this article. The experimental results indicate that the Internet bookstore recommendation system is feasible.

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Study the Personal Push Service of University Library Based on Big Data Mining

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.998-999.1261 ◽

2014 ◽

Vol 998-999 ◽

pp. 1261-1265 ◽

Cited By ~ 1

Author(s):

Cheng Yi ◽

Ying Xia ◽

Zhi Yong Zhang

Keyword(s):

Data Mining ◽

Big Data ◽

Association Rules ◽

Recommendation System ◽

Personalized Recommendation ◽

Data Resource ◽

Big Data Mining ◽

University Library ◽

Library Resources ◽

Classical Association

It expounds the big data and the relevant theoretical knowledge of big data mining, In view of the lack of effective analysis of the data resource access in delivery service of university library, this paper designs the personalized recommendation system service model of university library, with clustering analysis and association rules theory as the foundation of technology. And it introduces in detail how to cluster according to the user's attribute characteristics and how to introduce minimum support to opti-mize on the basis of the classical association rules algorithm. Experiments show that the improved algorithm can improves the utilization of library resources.

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Web Data Mining-Based Personalized Recommendation System

Advanced Research on Electronic Commerce, Web Application, and Communication - Communications in Computer and Information Science ◽

10.1007/978-3-642-20367-1_41 ◽

2011 ◽

pp. 261-265

Author(s):

Shengjiao Xu ◽

Tinggui Chen

Keyword(s):

Data Mining ◽

Recommendation System ◽

Personalized Recommendation ◽

Web Data ◽

Web Data Mining

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The Application Design of Personalized Recommendation System Based on Data Mining to E-Commerce

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.989-994.4538 ◽

2014 ◽

Vol 989-994 ◽

pp. 4538-4541 ◽

Cited By ~ 2

Author(s):

Li Sun

Keyword(s):

Data Mining ◽

Recommendation System ◽

Implementation Process ◽

The Other ◽

Personalized Recommendation ◽

Practical Application ◽

Application System ◽

Mining Project ◽

Function Modules ◽

Application Design

Personalized recommendation application system of product and service is a valid tool to boost sales in both online and offline business. It has been reported and has been our experience that algorithmic –modeling phase occupies at most 20% of the effort in a data–mining project. The other 80% is how to put the “model” into practical application. The implementation process of personalized recommendation system based on data mining to E-commerce was discussed in this paper. We also proposed architecture of the system, described the application of technology, designed some features of the function modules.

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