Consumer-Friendly Shopping Assistance by Personal Behavior Log Analysis on Ubiquitous Shop Space

Abstract

This paper has proposed a shopping assistance service. We provide consumer-friendly services which based on personal behavior log data. The consumer-friendly services are information service which display through a monitor, robot, sound and music that can attract new consumer. In this paper, we study personal behavior from a log file that has been recorded by RFID and camera sensors in the ubiquitous environment. Utilizing ubiquitous sensors, we apply three types of observation scopes to model each user's preference. They are microscopic, mezzoscopic, and macroscopic observation scopes. We have proposed the behavior analysis, algorithms and collaborative filtering to retrieve information. Finally, we will also propose a ubiquitous shop space experiment.

A Review of the Role of Sensors in Mobile Context-Aware Recommendation Systems

“…Then, it uses location-aware techniques to track the typical path of customers and so recommend items on their way. A more sophisticated approach is provided in [261], where the authors present a shopping assistant service based on customer's behavior log data. Their proposal uses ubiquitous sensors, such as RFID tags or cameras, to learn the personal behavior of the customers.…”

Shopping Center Tracking and Recommendation Systems

“…Sae-Ueng et al propose a consumer-friendly shopping assistance service based on personal behavior data in ubiquitous shopping spaces [14]. The system tries to study the personal behavior using RFID and camera sensors in the ubiquitous environment to build an user profile.…”