Paper Info
Title
Neural Networks and Business Applications: Business Intelligence
Abstract
Business data can be considered one of the most important asset of an enterprise. However a huge amount of data ranging from sales figures during a certain period of time to sales strategies is being generated and stored in data warehouses of enterprises. The point is then how to use that information efficiently and quickly in order to plan and to act in a highly competitive and globalised world. Many researchers call that process business intelligence. Neural networks can be used as data mining devices modeling the relationships present in business data and so enhance business intelligence in many business applications. We start the tutorial with an introduction of Neural Networks including a conceptual view and then show they can be used for prediction and classification in several business issues. Next, we describe the most used neural networks structures in business applications: the multilayered feedforward neural network and the self-organizing-map. The first structure is typically used for prediction problems such as stock market prediction, and the second for clustering data according to similarities such as customer behaviour analysis. Several examples are presented aiming to show how to achieve business intelligence using neural networks.
Year
Venue
Keywords
2006
ICEIS 2006: PROCEEDINGS OF THE EIGHTH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATIONAL SYSTEMS: DATABASES AND INFORMATION SYSTEMS INTEGRATION
neural network,business intelligence
Field
DocType
Citations 
Computer science,Knowledge management,Artificial neural network,Business intelligence,Business activity monitoring,Reactive search optimization
Conference
0
PageRank 
References 
Authors
0.34
1
2
Name
Order
Citations
PageRank
Pedro Henrique Gouvea Coelho157.74
Luiz Biondi Neto286.33