Knowledge Acquisition for Business Intelligent Systems

8 Pages Posted: 24 Dec 2009

See all articles by Ioan Andone

Ioan Andone

Alexandru Ioan Cuza University - Faculty of Economics and Business Administration

Napoleon-Alexandru Sireteanu

"Alexandru Ioan Cuza" University of Iasi, Faculty of Economics and Business Administration, Business Information Systems

Date Written: December 21, 2009

Abstract

Knowledge acquisition is a frequent bottleneck in business intelligent systems, and knowledge extraction from trained artificial neural networks (ANNs) provides an excellent way for explaining the functioning of a business connectionist system. This is important for ANNs to gain a wider degree of acceptance in problem domain applications like classification, diagnosis, continuous function approximation, time series prediction, and data mining. All these typical applications could be implemented into hybrid business intelligent systems. This paper presents the new applied research techniques for extracting business knowledge from trained ANNs, and it is organized into four sections that include an introduction, the state of the art, knowledge extraction and representation by rules, and conclusions.

Keywords: knowledge acquisition, trained neural networks, knowledge extraction, rules, business expert systems, hybrid intelligent systems

JEL Classification: C63, D83, L86

Suggested Citation

Andone, Ioan and Sireteanu, Napoleon-Alexandru, Knowledge Acquisition for Business Intelligent Systems (December 21, 2009). Available at SSRN: https://ssrn.com/abstract=1527724 or http://dx.doi.org/10.2139/ssrn.1527724

Ioan Andone (Contact Author)

Alexandru Ioan Cuza University - Faculty of Economics and Business Administration ( email )

Bd. Carol I no.22
Iasi, RO-700505
Romania

Napoleon-Alexandru Sireteanu

"Alexandru Ioan Cuza" University of Iasi, Faculty of Economics and Business Administration, Business Information Systems ( email )

Carol I Blvd, Nr.11
Lasi, 700506
Romania
400232201658 (Phone)

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