Improving Online Customer Shopping Experience with Computer Vision and Machine Learning Methods

Zequn Li, Honglei Li, Ling Shao

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)

Abstract

Computer vision and pattern recognition has achieved great developments in last decade, especially the feature categorizing and detection. How to exploit the new techniques in this research area has rarely discussed in the information systems field. This paper aims at exploring the opportunities from the most recent development from computer vision area from the online shopping experience perspective. We discussed the possibility of extracting meaningful information from images and apply this to the online recommendation system to improve online customer shopping experience. Implications to both researchers and practitioners are discussed. The contribution of these papers are twofold, firstly, we have summarized the state-of-the-art of the computer vision development in the online shopping recommendation system, especially in the fashion industry; secondly, we have provided some potential research gaps for on how computer vision method could be used in the information systems field.
Original languageEnglish
Title of host publicationHCI in Business, Government, and Organizations: eCommerce and Innovation
Place of PublicationLondon
PublisherSpringer
Pages427-436
Volume9751
ISBN (Print)978-3-319-39395-7
DOIs
Publication statusPublished - 2016

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