A Study on the Comparison between Content-Based and Preference-Based Recommendation Systems

Author

Chuang, Huan-Ming ; Wang, Li-Chuan ; Pan, Chu-Ching

Author_Institution

Dept. of Inf. Manage., Nat. Yunlin Univ. of Sci. & Technol., Taiwan

fYear

2008

fDate

3-5 Dec. 2008

Firstpage

477

Lastpage

480

Abstract

Since business markets have the feature of small number of customers with tremendous amount of sales, itÂ¿s quite cost-effective to offer personalized recommendations to enhance customer responsiveness and relationship marketing.Two current popular recommendation systems both from content- and preference-based approach are conducted to compare their recommendation quality.In sum, ARM performed better than RFM-CF in this case. It implied that itÂ¿ beneficial to segment customers, and then to provide customized services for different customer segments.

Keywords

customer relationship management; data mining; information filters; association rule mining; collaborative filtering method; content-based recommendation systems; customer relationship marketing; customer responsiveness; preference-based recommendation systems; recency frequency and monetary Analysis; Association rules; Automotive components; Collaboration; Companies; Data mining; Delay; Filtering; Frequency; Information management; Marketing and sales; Association Rules Mining(ARM); Collaborative Filter (CF); Data Mining; Personalized Recommendation;

fLanguage

English

Publisher

ieee

Conference_Titel

Semantics, Knowledge and Grid, 2008. SKG '08. Fourth International Conference on

Conference_Location

Beijing

Print_ISBN

978-0-7695-3401-5

Electronic_ISBN

978-0-7695-3401-5

Type

conf

DOI

10.1109/SKG.2008.89

Filename

4725968