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Neural Computing and Applications
Published in: Neural Computing and Applications 3-4/2003

01-12-2003 | Original Article

Optimising newspaper sales using neural-Bayesian technology

Authors: Tom Heskes, Jan-Joost Spanjers, Bart Bakker, Wim Wiegerinck

Published in: Neural Computing and Applications | Issue 3-4/2003

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Abstract

We describe a software system, called just enough delivery (JED), for optimising single-copy newspaper sales, based on a combination of neural and Bayesian technology. The prediction model is a huge feedforward neural network, in which each output corresponds to the sales prediction for a single outlet. Input-to-hidden weights are shared between outlets. The hidden-to-output weights are specific to each outlet, but linked through the introduction of priors. All weights and hyperparameters can be inferred using (empirical) Bayesian inference. The system has been tested on data for several different newspapers and magazines. Consistent performance improvements of 1 to 3% more sales with the same total amount of deliveries have been obtained.
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Metadata
Title
Optimising newspaper sales using neural-Bayesian technology
Authors
Tom Heskes
Jan-Joost Spanjers
Bart Bakker
Wim Wiegerinck
Publication date
01-12-2003
Publisher
Springer-Verlag
Published in
Neural Computing and Applications / Issue 3-4/2003
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-003-0384-x

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