文档介绍：A Bayesian work-driven Decision Support System for Client-
Server Implementation
Eitel . Lauría*
Peter J. Duchessi**
*School puter Science & Mathematics
Marist College
Poughkeepsie, NY, USA
Email: Eitel.******@
**School of Business
University at Albany, State University of New York
Albany, NY, USA
Email: p.******@
Abstract
Bayesian works (BBNs) are graphical models that provide pact and simple representation of
probabilistic data. BBNs depict the relationships among several variables and include conditional probability
distributions that can be used to make probabilistic statements about those variables. This paper demonstrates
how to create a BBN from real-world data on client-server implementations and provides a methodology for
organizing the data, and for applying several techniques and algorithms to learn work’s structure and
estimate the pertinent parameters. The paper also displays the resulting BBN and describes how it can be
incorporated into a DSS to support “what-if” analyses about client-server implementations.
Keywords
Information technology implementation, Bayesian works, and decision support systems
1. INTRODUCTION
Over the last two decades, information technology (IT) implementation has been the most researched IT topic.
This phenomenon is primarily due to the role IT plays