The University of Southampton
University of Southampton Institutional Repository

Future trends in business analytics and optimization

Future trends in business analytics and optimization
Future trends in business analytics and optimization
During the last decades, the disciplines of Data Mining and Operations Research have been working mostly independent of each other. However, the increasing complexity of today's applications in areas such as business, medicine, and science requires more and more interaction between both disciplines. On the one hand, several data mining algorithms are based on optimization methods. On the other hand, in several applications the pure Knowledge Discovery in Databases (KDD) process is not sufficient since it does not take explicitly into account the entire decision process. This report presents future trends in Business Analytics and Optimization discussed at the panel sessions during the workshop on Business Analytics and Optimization (BAO'2010).
future trends, business analytics and optimization, data mining, methodological research, real-life applications
1088-467x
1001-1017
Brown, D.E.
a2d96678-f273-4d52-bb5e-e07f18731e10
Famili, F.
2622be77-97ed-4bf8-bf2a-d0b9e6b90956
Paass, G.
9874445a-d236-4542-9f23-ba5fc99090ac
Smith-Miles, K.
ba853dd1-72a0-497f-88bb-1769830e262d
Thomas, L.C.
a3ce3068-328b-4bce-889f-965b0b9d2362
Weber, R.
d60b7a82-1576-464b-81b5-86d74b0574f5
Baeza_Yates, R.
7528f6d0-1380-40ef-8da0-745a81ad652b
Bravo, C.
2f518b2b-5e75-4874-9bfd-015277abc9d5
Huillier, G.
8f825cc2-c4bb-459a-acdb-fc72d6ab2b73
Maldonado, S.
09e6d75b-5084-405e-8e00-910716777ef0
Brown, D.E.
a2d96678-f273-4d52-bb5e-e07f18731e10
Famili, F.
2622be77-97ed-4bf8-bf2a-d0b9e6b90956
Paass, G.
9874445a-d236-4542-9f23-ba5fc99090ac
Smith-Miles, K.
ba853dd1-72a0-497f-88bb-1769830e262d
Thomas, L.C.
a3ce3068-328b-4bce-889f-965b0b9d2362
Weber, R.
d60b7a82-1576-464b-81b5-86d74b0574f5
Baeza_Yates, R.
7528f6d0-1380-40ef-8da0-745a81ad652b
Bravo, C.
2f518b2b-5e75-4874-9bfd-015277abc9d5
Huillier, G.
8f825cc2-c4bb-459a-acdb-fc72d6ab2b73
Maldonado, S.
09e6d75b-5084-405e-8e00-910716777ef0

Brown, D.E., Famili, F., Paass, G., Smith-Miles, K., Thomas, L.C., Weber, R., Baeza_Yates, R., Bravo, C., Huillier, G. and Maldonado, S. (2011) Future trends in business analytics and optimization. Intelligent Data Analysis, 15 (6), 1001-1017. (doi:10.3233/IDA-2011-0506).

Record type: Article

Abstract

During the last decades, the disciplines of Data Mining and Operations Research have been working mostly independent of each other. However, the increasing complexity of today's applications in areas such as business, medicine, and science requires more and more interaction between both disciplines. On the one hand, several data mining algorithms are based on optimization methods. On the other hand, in several applications the pure Knowledge Discovery in Databases (KDD) process is not sufficient since it does not take explicitly into account the entire decision process. This report presents future trends in Business Analytics and Optimization discussed at the panel sessions during the workshop on Business Analytics and Optimization (BAO'2010).

This record has no associated files available for download.

More information

e-pub ahead of print date: 18 November 2011
Keywords: future trends, business analytics and optimization, data mining, methodological research, real-life applications
Organisations: Centre of Excellence in Decision, Analytics & Risk Research

Identifiers

Local EPrints ID: 375186
URI: http://eprints.soton.ac.uk/id/eprint/375186
ISSN: 1088-467x
PURE UUID: a4708cf6-1474-4ed6-9d97-b8d131e7bff6

Catalogue record

Date deposited: 16 Mar 2015 13:25
Last modified: 14 Mar 2024 19:21

Export record

Altmetrics

Contributors

Author: D.E. Brown
Author: F. Famili
Author: G. Paass
Author: K. Smith-Miles
Author: L.C. Thomas
Author: R. Weber
Author: R. Baeza_Yates
Author: C. Bravo
Author: G. Huillier
Author: S. Maldonado

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×