Skip to main content
EXTENDED SEARCH
Log in
Top
Artificial Intelligence Review
Published in:

14-06-2018

A survey of machine learning techniques for food sales prediction

Author: Grigorios Tsoumakas

Published in: Artificial Intelligence Review | Issue 1/2019

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Food sales prediction is concerned with estimating future sales of companies in the food industry, such as supermarkets, groceries, restaurants, bakeries and patisseries. Accurate short-term sales prediction allows companies to minimize stocked and expired products inside stores and at the same time avoid missing sales. This paper reviews existing machine learning approaches for food sales prediction. It discusses important design decisions of a data analyst working on food sales prediction, such as the temporal granularity of sales data, the input variables to use for predicting sales and the representation of the sales output variable. In addition, it reviews machine learning algorithms that have been applied to food sales prediction and appropriate measures for evaluating their accuracy. Finally, it discusses the main challenges and opportunities for applied machine learning in the domain of food sales prediction.
previous article An introduction to brain emotional learning inspired models (BELiMs) with an example of BELiMs’ applications
next article Classification of asymptomatic and osteoarthritic knee gait patterns using gait analysis via deterministic learning

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Business + Economics & Engineering + Technology"

Online-Abonnement

Springer Professional "Business + Economics & Engineering + Technology" gives you access to:

  • more than 102.000 books
  • more than 537 journals

from the following subject areas:

  • Automotive
  • Construction + Real Estate
  • Business IT + Informatics
  • Electrical Engineering + Electronics
  • Energy + Sustainability
  • Finance + Banking
  • Management + Leadership
  • Marketing + Sales
  • Mechanical Engineering + Materials
  • Insurance + Risk


Secure your knowledge advantage now!

inform now

Springer Professional "Business + Economics"

Online-Abonnement

Springer Professional "Business + Economics" gives you access to:

  • more than 67.000 books
  • more than 340 journals

from the following specialised fileds:

  • Construction + Real Estate
  • Business IT + Informatics
  • Finance + Banking
  • Management + Leadership
  • Marketing + Sales
  • Insurance + Risk



Secure your knowledge advantage now!

inform now

Springer Professional "Engineering + Technology"

Online-Abonnement

Springer Professional "Engineering + Technology" gives you access to:

  • more than 67.000 books
  • more than 390 journals

from the following specialised fileds:

  • Automotive
  • Business IT + Informatics
  • Construction + Real Estate
  • Electrical Engineering + Electronics
  • Energy + Sustainability
  • Mechanical Engineering + Materials





 

Secure your knowledge advantage now!

inform now
Footnotes
This content is only visible if you are logged in and have the appropriate permissions.
Literature
This content is only visible if you are logged in and have the appropriate permissions.
Metadata
Title
A survey of machine learning techniques for food sales prediction
Author
Grigorios Tsoumakas
Publication date
14-06-2018
Publisher
Springer Netherlands
Published in
Artificial Intelligence Review / Issue 1/2019
Print ISSN: 0269-2821
Electronic ISSN: 1573-7462
DOI
https://doi.org/10.1007/s10462-018-9637-z

Other articles of this Issue 1/2019

Primary user characterization for cognitive radio wireless networks using a neural system based on Deep Learning

Local structure learning of chain graphs with the false discovery rate control

Using machine learning to predict student difficulties from learning session data

A review on deep learning for recommender systems: challenges and remedies

A wavelet-based hybrid neural network for short-term electricity prices forecasting

Deep ensemble network based on multi-path fusion

Premium Partner

    Image Credits