Deep Learning Techniques for Automation and Industrial Applications

13Collaborative Design and Case Analysis of Mobile Shopping Apps: A Deep Learning Approach

Santosh Kumar^*, Vipul Jain, Abhishek Bairwa and Pradeep Saharan

Department of Computer Science, Global Institute of Technology, Jaipur, India

Abstract

From the point of view of the user’s experience, this article engages in an in-depth analysis of associated ideas and challenges that arise in the process of shopping app interface design. It further demonstrates the functional simplicity, ease of use, and effectiveness that are centered on the experience of the user, and are built on an interactive model via the use of classical instances and practical design projects. After that, we use these theories, together with associated ideas in design psychology, behavior, design aesthetics, and ergonomics, to conduct a thorough study of mobile shopping apps interaction design. It divides mobile shopping apps via the process of “global-local-global” into repeated personalized interactive designs, and it gives reference, effective recommendations, and ideas for the construction of mobile and vertical shopping apps. Additionally, it includes particular analysis and data collection in practical instances.

This research chapter is partially or we can say directly related to deep learning. It also highlights the potential applications of deep learning techniques within mobile shopping apps. Deep learning can be utilized to analyze user behavior data, enabling personalized recommendations and improving ...