Improving Online Customer Shopping Experience with Computer Vision
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 study 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. Most existing online recommendation systems are making recommendations based text tags leaving large information from images un-used. Machine learning algorithm can use used to extract meaningful information such as texture, colour, and style information and classify them into different categories. This research will benefit those websites especially for that pure e-commerce website relying on online recommendation systems.
Dr. Honglei Li is currently a senior lecturer in Enterprise Information Systems at Department of Computing & Information Sciences, Northumbria University. Holding a PhD and M.Phil in Management Information Systems and a BSC in computational mathematics, she is enthusiastic about transforming our life through new technologies. She has been working on several research projects including Improving Shopping Experience with Image Processing Technology, Creating Digital Government Platform for Better Public Engagement, Smart City, and Virtual Community Participation through Interpersonal Relationships. She is an active researcher publishing papers in top journals such as Information & Management and Internet Research.