AbstractsBusiness Management & Administration

Understanding the customer s requirements and purchasing newlinebehaviour is becoming more and more important in retail as it may provide newlinevaluable information that can be used to improve customer s shopping newlineexperience and product sales Knowing about customers activities within the newlinestore can provide information for improving customer relationship newlinemanagement and including real time capabilities This research work presents newlinea scheme for mining frequent movement path sequences using shopping path newlinetracking and analysis system that uses RFID The collected data is used for newlinedetermining customer presence and movement through a store as well as time newlinespent in specific store segments newlineRetrieving frequent walking patterns of the customers among newlinedifferent locations in the large retail outlet reveals the most visited spots and newlinemovements of the customer This helps in identifying the purchase behaviour newlineof the customers Data mining techniques are used to discover all frequent newlinewalking patterns efficiently from cleaned RFID database The existing newlineapproaches are expensive in terms of time and memory usage The research newlinestudy proposed AFP Tree and ECIM Efficient Closed Item set Mining newlinealgorithms to discover the frequent walking patterns from RFID database newline newline%%%reference p160-167.