Cognition-Driven Decision Support for Business Intelligence [electronic resource] : Models, Techniques, Systems and Applications / by Li Niu, Jie Lu, Guangquan Zhang.

Concepts -- Decision Making and Decision Support Systems -- Business Intelligence -- Managerial Cognition -- Cognition in Business Decision Support Systems -- Models -- Cognition-Driven Decision Processes -- Techniques -- Domain Knowledge Representation and Processing -- Natural Language Processing for Situation Awareness -- Data Warehouse Query Construction and Situation Presentation -- Systems and Applications -- A Cognition-Driven Decision Support System: FACETS -- Evaluation of Algorithms and FACETS -- Application Cases of FACETS.

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 todays 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 managers SA input; extraction of SA semantics; construction of data warehouse queries based on the mangers SA and experience; situation information retrieval from data warehouse; how the manager perceives situation information and update SA; how the managers SA leads to a final decision. Finally, a cognition-driven DSS, FACETS, and two illustrative applications of this system are discussed.

ZDB-2-ENG