Incorporates ANN, Fuzzy and Evolutionary approaches, and more especially hybrids of these (some authors extend this definition to include intelligent agents, stochastic reasoning and other techniques).
Published in Chapter:
Intelligent Information Systems
John Fulcher (University of Wollongong, Australia)
Copyright: © 2009
|Pages: 8
DOI: 10.4018/978-1-60566-026-4.ch333
Abstract
Information Systems (IS), not surprisingly, process information (data + meaning) on behalf of and for the benefit of human users. Information Systems comprise the basic building blocks shown in Figure 1, and as such can be likened to the familiar Von Neumann computer architecture model that has dominated computing since the mid 20th Century. In practice, IS encompass not just computer system hardware (including networking) and software (including DataBases), but also the people within an organization (Stair & Reynolds, 1999). Information Systems are ubiquitous in today’s world–the so-called “Digital Age”–and are tailor-made to suit the needs of many different industries. The following are some representative application domains: • Management Information Systems (MIS) • Business IS • Transaction processing systems (& by extension, eCommerce) • Marketing/Sales/Inventory IS (especially via the Internet) • Postal/courier/transport/fleet/logistics IS • Geographical Information System (GIS)/Global Positioning Satellite (GPS) systems • Health/Medical/Nursing IS The roles performed by IS have changed over the past few decades. More specifically, whereas IS focussed on data processing during the 1950s and 1960s, management reporting in the 1960s and 1970s, decision support during the 1970s and 1980s, strategies and end user support during the 1980s and 1990s, these days (the early years of the 21st Century) they focus more on global Internetworking (O’Brien, 1997). Accordingly, we nowadays find extensive use of IS in e-business, decision support, and business integration (Malaga, 2005). Let us take a closer look at one of these–Decision Support Systems. A DSS consists of (i) a (Graphical) User Interface, (ii) a Model Management System, and (iii) a Data Management System (comprising not only Data/Knowledge Bases but also Data Warehouses, as well as perhaps incorporating some Data Mining functionality). The DSS GUI typically displays output by way of text, graphs, charts and the like, enabling users to visualize recommendations/advice produced by the DSS. The Model Management System enables users to conduct simulations, perform sensitivity analysis, explore “what-if” scenarios (in a more extensive manner than what we are familiar with in spreadsheets), and so forth.