SHOPPING PATH ANALYSIS AND TRANSACTION MINING BASED ON RFID TECHNOLOGY.
ABSTRACT : The active RFID technology is gaining strong support from business for various applications such as supply chain management, access control, air line luggage management, etc Due to the cost consideration, it is still not a replacement for the traditional item-level Bar-code. Therefore, tracking and analyzing the shopping path and purchasing behaviors of customers in a superstore such as Wl Maart is still a challenging task.
In this project, a practical attempt have made a RFID deployment model for collecting shopping paths and purchased items of customers. Algorithms based on customer Access Matrix (CAM) and Customer Transaction Mining (CTM) is then proposed for mining preferred shopping paths and their relationships to the purchased items. In the experiments, we build a data set generator for shopping paths and purchased items of customers, and the results show that our model is applicable to real time application.
Implementation: In this system, multiple active tags are used. Each tag can be used again, so the data in the tag is easily reprogrammable as per the application. The base unit has reader and processor, which is connected to a PC with database. Multiple tags can be added to the system as per the cost estimation.