DocumentCode :
2939415
Title :
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
Link To Document :
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