Title: Mining of customer walking path sequence from RFID supermarket data

Authors: Koppula Srinivas Rao; K.R. Chandran

Addresses: Department of CSE, CMR College of Engineering and Technology, Hyderabad, Andhra Pradesh 501401, India; Department of Information and Communication Engineering, Anna University, Chennai, Tamilnadu 600025, India ' Department of Computer and Information Sciences, PSG College of Technology, Coimbatore 641 004, Tamilnadu, India

Abstract: A fundamental problem with huge potential advantages for object tracking, product procurement processes and customer movement is the storage and extraction of information from RFID datasets. In this paper, we have designed an efficient technique for tracking the customers' walking path sequences using RFID equipped data. The frequent walking path sequences of the customers' movement have been extracted by exposing the most visited areas and walks across the warehouse and the typical products selected along the way. We make use of synthetic RFID datasets to experiment the proposed technique. From the analysis, we showed that the run time and memory usage is outperformed likely by 50% than the previous method. The applications such as analysing the sequential behaviour in telecommunication, market basket analysis, medical data analysis and electronic government used the sequential pattern mining methods.

Keywords: data mining; sequential pattern mining; sequential patterns; RFID data; RFID readers; RFID tags; walking path sequences; e-government; customer walking paths; supermarket data; supermarkets; object tracking; product procurement; customer movement; electronic government.

DOI: 10.1504/EG.2013.051278

Electronic Government, an International Journal, 2013 Vol.10 No.1, pp.34 - 55

Published online: 03 Jan 2013 *

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