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Pizza sales forecasting using big data analysis

Authors
Lee, DaebumKim, Juntae
Issue Date
May-2015
Publisher
International Information Institute Ltd.
Keywords
Big data mining; Data mining algorithms; Sales forecasting
Citation
Information (Japan), v.18, no.5, pp 1577 - 1584
Pages
8
Indexed
SCOPUS
Journal Title
Information (Japan)
Volume
18
Number
5
Start Page
1577
End Page
1584
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/20033
ISSN
1343-4500
Abstract
In today's business environments analysis of big data offers quite remarkable advantage for businesses over their competitors. This study gathers and analyzes big data to propose a pizza sales forecasting model. To that end, the past sales data, and data of events such as holidays, weather, news articles, economic indices, trends, and sports were gathered and used. Sales forecasting methods such as regression analysis and artificial neural network learning model were used to compare the accuracy of forecasting in the presence and absence of collected big data. Experiment results found that the forecasting error rate was improved by over 5% when using big-data.. ©2015 International Information Institute.
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