General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • E-mail: ijcte@iacsitp.com
    • Journal Metrics:

Editor-in-chief
Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2012 Vol.4(5): 694-696 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2012.V4.559

A New Method for Compressing Massive RFID Data to Achieve Efficient Mining

L. Hafezi, M. H. Saraee, and M. A. Montazeri

Abstract—Radio Frequency Identification (RFID) technology has been used for many purposes and has had effective results. This technology eases and accelerates many applications, but it has proposed a challenge, and that is the production of such a volume of data. The volume is so enormous that disusing the system comes into consideration. However different methods have been applied for solving this problem. In this paper, we propose a new method for data compression without missing any data. By applying it to our system, a production line of car engines, we can get our data to 1/50 times the basic data. We can also return to the basic data. We apply data mining to estimate the accuracy of our method and we consider our method error rate is 16 percent that is acceptable.

Index Terms—Data compression, data mining, RFID technology.

The authors are with the Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran (e-mail: l.hafezi@ec.iut.ac.ir, Saraee@cc.iut.ac.ir, Montazeri@cc.iut.ac.ir ).

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Cite: L. Hafezi, M. H. Saraee, and M. A. Montazeri, "A New Method for Compressing Massive RFID Data to Achieve Efficient Mining," International Journal of Computer Theory and Engineering vol. 4, no. 5, pp.  694-696, 2012.


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