DocumentCode :
2150959
Title :
Revealing sales trends through data mining
Author :
Plessas-Leonidis, Spyros ; Leopoulos, Vrassidas ; Kirytopoulos, Konstantinos
Author_Institution :
Mech. Eng. Dept., Nat. Tech. Univ. of Athens, Athens, Greece
Volume :
1
fYear :
2010
fDate :
26-28 Feb. 2010
Firstpage :
682
Lastpage :
687
Abstract :
Data mining is defined as the process of discovering patterns in data. This paper presents a case study of the implementation of data mining techniques in revealing sales trends within the publishing industry. Conclusions of this research, based on successful and unsuccessful trials, indicate that data mining is indeed a valuable tool, however, selection of the appropriate variables - data to be used in relevant models is the only parameter that can define the predictive success or not of the algorithms.
Keywords :
data mining; pattern clustering; publishing; data mining; data patterns; publishing industry; revealing sales trends; valuable tool; Data mining; Economic forecasting; Engineering management; Financial management; Marketing and sales; Mechanical engineering; Mining industry; Predictive models; Pricing; Publishing; case study; data mining; sales forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-5585-0
Electronic_ISBN :
978-1-4244-5586-7
Type :
conf
DOI :
10.1109/ICCAE.2010.5451296
Filename :
5451296
Link To Document :
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