Style matching model-based recommend system for online shopping

Author

Zhao, Guannan ; Luo, Shijian ; He, Ji

Author_Institution

Coll. of Comput. Sci. & Technol., Zhejiang Univ., Hangzhou, China

fYear

2009

fDate

26-29 Nov. 2009

Firstpage

1995

Lastpage

1999

Abstract

In order to enrich the recommendation of e-commerce functionality and optimize the user experience of online shopping, a new style matching model-based recommend method of e-commerce was proposed. The Content-Based Image Retrieval (CBIR) technology was used to extract the image feature of color, texture and shape of product, calculated the commodity cluster, which have the similar feature of image content, then was applied to the style matching model, recommend to the user in accordance with the user´s cognitive style. The style matching mode-based recommendation engine was developed, and integrated into the e-commerce recommend system to help users complete the cognitive of style and guide the online shopping. Finally, a shoe buying recommend system was developed to verify the theory.

Keywords

content-based retrieval; electronic commerce; feature extraction; image colour analysis; image retrieval; image texture; recommender systems; retail data processing; commodity cluster; content-based image retrieval; e-commerce functionality; image feature extraction; online shopping; product color; product shape; product texture; shoe buying recommend system; style matching model-based recommend system; Content based retrieval; Data mining; Feature extraction; Feedback; Helium; Image databases; Image retrieval; Information retrieval; Search engines; User interfaces; E-commerce; Image Retrieval; Recommend system; Style matching model;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer-Aided Industrial Design & Conceptual Design, 2009. CAID & CD 2009. IEEE 10th International Conference on

Conference_Location

Wenzhou

Print_ISBN

978-1-4244-5266-8

Electronic_ISBN

978-1-4244-5268-2

Type

conf

DOI

10.1109/CAIDCD.2009.5375128

Filename

5375128