Applying computational intelligence methods for predicting the sales of newly published books in a real editorial business management environment
作者：
Highlights：
• The problem of predicting total sales, to print the right amount of books, is faced.
• A methodology to analyse data related to book sales prediction is proposed.
• A feature selection process is conducted to find out the main factors influencing sales.
• Real world data is analysed using several data mining and visualisation techniques.
• Obtained models are able to predict sales from pre-publication data.
• Predictive models to be used as decision-aid tools for book publishers are presented.
摘要
•The problem of predicting total sales, to print the right amount of books, is faced.•A methodology to analyse data related to book sales prediction is proposed.•A feature selection process is conducted to find out the main factors influencing sales.•Real world data is analysed using several data mining and visualisation techniques.•Obtained models are able to predict sales from pre-publication data.•Predictive models to be used as decision-aid tools for book publishers are presented.
论文关键词：Book sales forecasting,Decision-aid models,Feature selection,Regression
论文评审过程：Received 3 June 2016, Revised 12 September 2016, Accepted 16 October 2016, Available online 17 October 2016, Version of Record 18 November 2016.
论文官网地址：https://doi.org/10.1016/j.knosys.2016.10.019
