Developing a Framework for Integrating Knowledge Management and Decision Support Systems: Application to Time Series Forecasting

Gonca Gulser,Bertan Badur

doi:10.5171/2011.137658

Abstract

Developing a Framework for Integrating Knowledge Management and Decision Support Systems: Application to Time Series Forecasting

Highlights

Decision Support Systems (DSS), which provide support to managers for solving semi or ill-structured problems, are becoming more important to organizations in their short and long term business decisions (Turban et al, 2007 and Courtney, 2001)
The explicit knowledge is composed of artificial neural networks (ANN) parameters and symbolic rules that are extracted from ANN models
We demonstrate the symbolic rule extraction from neural networks, to fill the model base

Summary

Introduction

Decision Support Systems (DSS), which provide support to managers for solving semi or ill-structured problems, are becoming more important to organizations in their short and long term business decisions (Turban et al, 2007 and Courtney, 2001). It is clear that classic DSS are insufficient to provide hidden knowledge in information and utilize selfadjustable models that can accord the more accurate and advance decision making process (Ergazakis et al, 2002 and Ergazakis et al, 2008). This situation leads us to a new decision support concept that integrates the processes of both knowledge management (KM) and DSS by using knowledge discovery techniques (KDT), (Nemati et al, 2002)

Objectives

Methods

Conclusion