Applying computational intelligence methods for predicting the sales of newly published books in a real editorial business management environment
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- 作者：Pedro A. Castillo ; a ; pacv@ugr.es" class="auth_mail" title="E-mail the corresponding author ; Antonio M. Moraa ; amorag@geneura.ugr.es" class="auth_mail" title="E-mail the corresponding author ; Hossam Farisb ; hossam.faris@ju.edu.jo" class="auth_mail" title="E-mail the corresponding author ; J.J. Mereloa ; jmerelo@geneura.ugr.es" class="auth_mail" title="E-mail the corresponding author ; Pablo Garcí ; a-Sá ; ncheza ; pablogarcia@ugr.es" class="auth_mail" title="E-mail the corresponding author ; Antonio J. Ferná ; ndez-Aresa ; antares.es@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Paloma De las Cuevasa ; palomacd@ugr.es" class="auth_mail" title="E-mail the corresponding author ; Marí ; a I. Garcí ; a-Arenasa ; mgarenas@ugr.es" class="auth_mail" title="E-mail the corresponding author
- 关键词：Book sales forecasting ; Decision-aid models ; Feature selection ; Regression
- 刊名：Knowledge-Based Systems
- 出版年：2017
- 出版时间：1 January 2017
- 年：2017
- 卷：115
- 期：Complete
- 页码：133-151
- 全文大小：2380 K
文摘
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The problem of predicting total sales, to print the right amount of books, is faced.
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A methodology to analyse data related to book sales prediction is proposed.
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A feature selection process is conducted to find out the main factors influencing sales.
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Real world data is analysed using several data mining and visualisation techniques.
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Obtained models are able to predict sales from pre-publication data.
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Predictive models to be used as decision-aid tools for book publishers are presented.