A Text Mining-based Recommendation System for Customer Decision Making in Online Product Customization

Author

Ittoo, Ashwin Ravi ; Zhang, Yiyang ; Jiao, Jianxin Roger

Author_Institution

Sch. of Inf. & Commun. Technol., Republic Polytech.

Volume

1

fYear

2006

fDate

21-23 June 2006

Firstpage

473

Lastpage

477

Abstract

This paper presents a text mining-based recommendation system to assist customer decision making in online product customization. The proposed system allows customers to describe their interests in textual format, and thus to capture customers´ preferences to generate accurate recommendations. The system employs text mining techniques to learn product features, and accordingly recommends products that match the customers´ preferences. The effectiveness of the suggested recommendation methodology is validated by experimental evaluations

Keywords

Internet; customer services; data mining; decision making; information filters; text analysis; customer decision making; customer preference; mass customization; online product customization; recommendation system; text mining; Association rules; Collaboration; Customer profiles; Data mining; Decision making; Filtering; Natural languages; Product customization; Scalability; Text mining; Recommendation System; customer preference; decision making; mass customization; text mining;

fLanguage

English

Publisher

ieee

Conference_Titel

Management of Innovation and Technology, 2006 IEEE International Conference on

Conference_Location

Singapore, China

Print_ISBN

1-4244-0147-X

Electronic_ISBN

1-4244-0148-8

Type

conf

DOI

10.1109/ICMIT.2006.262208

Filename

4035880