Handbook on Decision Support Systems 1: Basic ThemesFrada Burstein, Clyde W. Holsapple Springer Science & Business Media, 2008. gada 22. janv. - 854 lappuses Decision support systems have experienced a marked increase in attention and importance over the past 25 years. The aim of this book is to survey the decision support system (DSS) field covering both developed territory and emergent frontiers. It will give the reader a clear understanding of fundamental DSS concepts, methods, technologies, trends, and issues. It will serve as a basic reference work for DSS research, practice, and instruction. To achieve these goals, the book has been designed according to a ten-part structure, divided in two volumes with chapters authored by well-known, well-versed scholars and practitioners from the DSS community. |
No grāmatas satura
1.5. rezultāts no 58.
... reasoning knowledge and inference capabilities to help decision makers in much the same way as human experts/advisors can support decision making. Another class involves software agents, also called softbots or knowbots, which undertake ...
... reasoning, as well as knowledge about the state of some domain of interest (i.e., information). When a manager plays a monitor role, he/she seeks and acquires knowledge of his/her organization and its environment. Acting as a ...
... reasoning knowledge Bonczek et al. 1981, Holsapple and Whinston 1987, 1988, Holsapple 1995, Holsapple and Whinston 1996 Orientation Domain versus relational versus self knowledge Dos Santos and Holsapple 1989; Holsapple and Whinston ...
... reasoning knowledge (Holsapple and Whinston 1988, 1996, Holsapple 1995). Categories of secondary, derivative types of knowledge have also been identified; these include linguistic, assimilative, and presentation knowledge (Holsapple and ...
... reasoning (Holsapple and Whinston 1988, 1996). An instance of reasoning knowledge specifies what conclusion is valid or what action can be taken when a particular situation exists. The connection between the situation and the conclusion ...
Saturs
Systems for Supporting Marketing Decisions | 395 |
The Nature of Organizational Decision Support Systems | 415 |
CHAPTER 44 | 430 |
CHAPTER 22 | 433 |
Developing Practical Decision Support Tools Using Dashboards | 454 |
CHAPTER 23 | 469 |
Decision Support Systems in Forest Management | 499 |
CHAPTER 24 | 511 |
CHAPTER 8 | 141 |
CHAPTER 9 | 163 |
VARIATIONS | 170 |
Integrated Document Management for Decision Support 191 | 190 |
CHAPTER 11 | 207 |
CHAPTER 12 | 231 |
CHAPTER 13 | 259 |
SpreadsheetBased Decision Support Systems | 277 |
CHAPTER 15 | 299 |
WebBased Decision Support | 315 |
CHAPTER 17 | 341 |
Predicting Facilitating and Managing Knowledge Evolution | 345 |
A Motivational Model of Knowledge Sharing | 355 |
CHAPTER 19 | 371 |
Artificial Neural Networks in Decision Support Systems | 557 |
DSS Experience in Africa Cases from Egypt | 559 |
Data Mining and Data Fusion for Enhanced Decision Support | 581 |
CHAPTER 56 | 603 |
CHAPTER 28 | 609 |
Decision Support Based on Process Mining 637 | 636 |
Towards Decision Support for Participatory Democracy | 651 |
CHAPTER 30 | 659 |
CHAPTER 31 | 697 |
DECISION SUPPORT | 718 |
CHAPTER 34 | 763 |
Systems for Strategic Learning 759 | 829 |
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Handbook on Decision Support Systems 1: Basic Themes Frada Burstein,Clyde W Holsapple Priekšskatījums nav pieejams - 2016 |