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Mining of customer walking path sequence from RFID supermarket data

Mining of customer walking path sequence from RFID supermarket data 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Electronic Government, an International Journal Inderscience Publishers

Mining of customer walking path sequence from RFID supermarket data

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1740-7494
eISSN
1740-7508
DOI
10.1504/EG.2013.051278
Publisher site
See Article on Publisher Site

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.

Journal

Electronic Government, an International JournalInderscience Publishers

Published: Jan 1, 2013

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