The development of a research, teaching, or application of competitive (economic) intelligence requires a strategic and transverse vision in regards to related issues. It is essential to integrate the role of culture when interpreting results, either from the training of a specialist or in respect t
Competitive Intelligence and Decision Problems
✍ Scribed by Amos David
- Publisher
- Wiley-ISTE
- Year
- 2011
- Tongue
- English
- Leaves
- 362
- Series
- ISTE
- Category
- Library
No coin nor oath required. For personal study only.
✦ Synopsis
The development of a research, teaching, or application of competitive (economic) intelligence requires a strategic and transverse vision in regards to related issues. It is essential to integrate the role of culture when interpreting results, either from the training of a specialist or in respect to a country or region. The authors of this book, members of an expert group supported by the CNRS in France, bring all of their talents together to create a comprehensive book that does just this and more.
📜 SIMILAR VOLUMES
Cover; Competitive Intelligence and Decision Problems; Title Page; Copyright Page; Table of Contents; PART 1. MODELS AND TOOLS; Chapter 1. Model Use: From a Decision-Making Problem to a Set of Research Problems; 1.1. Introduction: why model?; 1.2. General presentation of the Watcher Information Sear
<p><p></p><p>This book includes 46 scientific papers presented at the conference and reflecting the latest research in the fields of data mining, machine learning and decision-making. The international scientific conference “Intellectual Systems of Decision-Making and Problems of Computational Intel
1 Prospects for knowledge-based robots.- 2 Robots and artificial intelligence: parallel developments.- 3 Expert systems and knowledge-based languages.- 4 Production-rule expert systems.- 5 Introduction to search techniques.- 6 Heuristic graph searching.- 7 AND/OR graphs.- 8 First order predicate log
<p><b>Presents </b><b>recent advances in both models and systems for intelligent decision making.</b></p><p>Organisations often face complex decisions requiring the assessment of large amounts of data. In recent years Multicriteria Decision Aid (MCDA) and Artificial Intelligence (AI) techniques have