Clustering Technology Application in e-Commerce Recommendation System

Author

Jinghui Wu ; Qiang Liu ; Siwen Luo

Author_Institution

Jiangxi key Lab. of Data & Knowledge Eng., Jiangxi Univ. of Finance & Econ., Nanchang

fYear

2008

fDate

17-19 Oct. 2008

Firstpage

200

Lastpage

203

Abstract

This article analyses two kinds of information filtering technologies used in the e-commerce recommendation system: content-based filtering and collaborative filtering. On the foundation of collaborative filtering, we research the influential role of cluster technology to improve the recommendation system quality, to reduce the computation complexity, and to enhance the system real-time response speed.

Keywords

electronic commerce; information filtering; clustering technology application; collaborative filtering; computation complexity; content-based filtering; e-commerce recommendation system; information filtering technology; real-time response speed; Collaboration; Conference management; Data mining; Electronic commerce; Financial management; Information filtering; Information filters; Knowledge management; Matched filters; Technology management; Clustering; Collaborative Filtering; Electronic commerce; Recommendation System;

fLanguage

English

Publisher

ieee

Conference_Titel

Management of e-Commerce and e-Government, 2008. ICMECG '08. International Conference on

Conference_Location

Jiangxi

Print_ISBN

978-0-7695-3366-7

Type

conf

DOI

10.1109/ICMECG.2008.31

Filename

4656625

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3172688