© 2009

Cognition-Driven Decision Support for Business Intelligence

Models, Techniques, Systems and Applications


Part of the Studies in Computational Intelligence book series (SCI, volume 238)

Table of contents

  1. Front Matter
  2. Concepts

    1. Front Matter
      Pages 1-1
    2. Li Niu, Jie Lu, Guangquan Zhang
      Pages 3-18
    3. Li Niu, Jie Lu, Guangquan Zhang
      Pages 19-29
    4. Li Niu, Jie Lu, Guangquan Zhang
      Pages 31-37
    5. Li Niu, Jie Lu, Guangquan Zhang
      Pages 39-50
  3. Models

    1. Front Matter
      Pages 51-51
    2. Li Niu, Jie Lu, Guangquan Zhang
      Pages 53-73
  4. Techniques

    1. Front Matter
      Pages 75-75
    2. Li Niu, Jie Lu, Guangquan Zhang
      Pages 77-96
    3. Li Niu, Jie Lu, Guangquan Zhang
      Pages 97-118
    4. Li Niu, Jie Lu, Guangquan Zhang
      Pages 119-139
  5. Systems and Applications

    1. Front Matter
      Pages 141-141
    2. Li Niu, Jie Lu, Guangquan Zhang
      Pages 143-156
    3. Li Niu, Jie Lu, Guangquan Zhang
      Pages 157-177
    4. Li Niu, Jie Lu, Guangquan Zhang
      Pages 179-214
  6. Back Matter

About this book


Cognition-driven decision support system (DSS) has been recognized as a paradigm in the research and development of business intelligence (BI). Cognitive decision support aims to help managers in their decision making from human cognitive aspects, such as thinking, sensing, understanding and predicting, and fully reuse their experience. Among these cognitive aspects, decision makers’ situation awareness (SA) and mental models are considered to be two important prerequisites for decision making, particularly in ill-structured and dynamic decision situations with uncertainties, time pressure and high personal stake. In today’s business domain, decision making is becoming increasingly complex. To make a successful decision, managers’ SA about their business environments becomes a critical factor.

This book presents theoretical models as well practical techniques of cognitiondriven DSS. It first introduces some important concepts of cognition orientation in decision making process and some techniques in related research areas including DSS, data warehouse and BI, offering readers a preliminary for moving forward in this book. It then proposes a cognition-driven decision process (CDDP) model which incorporates SA and experience (mental models) as its central components. The goal of the CDDP model is to facilitate cognitive decision support to managers on the basis of BI systems. It also presents relevant techniques developed to support the implementation of the CDDP model in a BI environment. Key issues addressed of a typical business decision cycle in the CDDP model include:

  • natural language interface for a manager’s SA input;
  • extraction of SA semantics;
  • construction of data warehouse queries based on the manger’s SA and
  • experience;
  • situation information retrieval from data warehouse;
  • how the manager perceives situation information and update SA;
  • how the manager’s SA leads to a final decision.

Finally, a cognition-driven DSS, FACETS, and two illustrative applications of this system are discussed.


algorithm algorithms business intelligence cognition data warehouse information retrieval knowledge knowledge representation linear optimization model semantics

Authors and affiliations

  1. 1.Fac. Information TechnologyUniversity of Technology Sydney (UTS)BroadwayAustralia

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