CS318 Decision Support Systems Rationale: This course aims to provide students with fundamental knowledge on decision support systems for managers and IS developers. This discipline is a combination of several different disciplines: mathematical models, database systems, expert systems, neural networks, data mining, operations research, management science, user interface, graphics techniques and programming techniques.

Course Outline: PART A IManagement support systems: An Overview  1. Managers and Computerized Support  2. Decision Support Systems (DSS)  3. Development process of a DSS IISystems, Mathematic Models, and Decision Support  1. Systems  2. Models  3. The Modeling Process  4. Critical Success Factors  5. Human Cognition and Decision Styles  6. Making Decision in Group IIIDecision Support Systems : An Overview  1. The Illustrative case for DSS  2. Introduction: What is a DSS;  3. Characteristic and Capabilities of DSS  4. Components of DSS  5. Classification of DSS and Their Support

IVData Management  1 Sources of Data  2. atabase and Database Management Systems: An Introduction  3 Fourth-generation Systems  4 Object-oriented Databases  5.Enterprise Decision Support and The Information Warehouse  6.Intelligent Databases VModeling and Model Management  1. Modeling in MSS  2. Static and Dynamic Models  3. Treating Certainty, Uncertainty, and Risk  4. Types of Modeling: Decision Trees, Mathematical Programming, Simulation, Heuristic Programming, Influence Diagrams, Forecasting, Spreadsheet, Multi- dimensional Modeling  5. Model Base Structure and Management VIUser Interface  1. User Interfaces: An Overview  2. Interface Modes (Styles): Graphics and Graphical User Interface (GUI), Multimedia and Hypermedia, Visual Interactive Modeling, Virtual Reality  3. Geographical Information System (GIS)  4. Natural Language Processing: An Overview and Methods  5. Research on User Interface in MSS

VIIConstructing a Decision Support System  1. Development Strategies  2. The DSS Development Process: Life Cycle versus Prototyping  3. Team-developed versus User-developed DSS  4. End-User Computing and User-developed DSS  5. Selection of a DSS Generator and Other Software Tools  6. Developing DSS in the Windows Environment PART B VIIIData Warehousing  1. Basic concepts of data warehousing  2. Data warehouse architectures  3. Some characteristics of data warehouse data  5. The reconciled data layer  6. Data tranformation  7. The derived data layer  8. The user interface IXData Mining  Overview on data mining  Association rules  Classification  Clustering  Some other data mining problems

XNeural Networks in Decision Support  1. Introduction  2. ANN representations  3. Perceptron Training  4. Multilayer networks and Backpropagation algorithm  5. Remarks on the Backpropagation algorithm  6. Neural network application development  7. Benefits and limitations of ANN  8. ANN Applications in decision support References [1] Turban, E., Aronson,J.E., Decision Support Systems and Intelligent Systems- 6th Edition, Prentice-Hall, Instructors: Part A: Dr. Le Van Duc Part B: Assoc. Prof. Dr. Duong Tuan Anh