Context Proceduralization in Decision Making

International Journal of Decision Support System Technology, 2009

Our objective is to support decision makers for improving their behavior. Behavior modeling imposes to tackle raw data (e.g., eye movement) as well as cognitive activity (e.g. preferences). This supposes to use a combination of a bottom-up approach and a top-down approach. This work was initiated in a project aiming to improve car-drivers' situation awareness in the domain of road safety. We present the lessons learned and discuss the part that can be of interest in other domains. In our context-based methodology, we establish a conceptual description of behaviors that addresses the initial objective of behavior management. The instantiation of this description allows identifying the classes of interest for the objective. Moreover, we develop two spaces, namely a behavior space and a situation space for representing how we couple the top-down and bottom-up approaches. We then identify the "expected behavior" of a decision maker to determine the types of errors associated with the initial class. A first validation is realized by the comparison of the "expected" and "effective" behaviors, and proposing scenarios with the same errors but in different contexts makes a second one. First results confirm the interest of the context-based methodology for our application in road safety, and in other domains where it is more important to work on behaviors of decision makers than decision makers themselves.

European Journal of Information Systems, 1997

With increasing integration of computer systems through local and wide area communication networks, there exists the capability in many organizations to retrieve information from databases to support ad hoc decision making by many different users. The idea that information is a corporate resource is now something more than business school hype. But the implications of sharing data are only just dawning on the corporate mind. How do managers interpret data? Where decision making is carried out by several people, perhaps in several different locations for different purposes the same data is used in multiple decision contexts. This paper explores the role of context as a way of adding value to information from databases. Two types of context are defined and discussed in relation to some examples of decisions where the role of context is vital. These examples are taken from some empirical research conducted with users of spatial decision support systems. Here the use of background information on maps, for example roads, add context to maps which otherwise simply display statistical data. The paper concludes by suggesting a model of context based on the notion that context acts as a filter between user and database.

Multiple lines of research in cognitive science have brought insight on the role that internal (cognitive) representations of situational context play in framing decision making and in differentiating expert versus novice decision performance. However, no single framework has emerged to integrate these lines of research, particularly the views from narrative reasoning research and those from situation awareness and recognition-primed decision research.

Encyclopedia of Decision Making and Decision Support Technologies

Many researchers have noted the high levels of abstraction required by the representation and conceptualisation of organisational decisions when these involve more than just simple operational concerns. They have concluded that the difficulty in specifying decisions problems in tangible terms at the early stages of a decision making process makes the analysis of DSS requirements difficult with current methods. If this observation is correct, it means that, despite substantial progress in technology, for example, quicker database engines, better graphical user interfaces, more flexible development platforms, and so forth, DSS developers may not be better equipped now than they were at the beginning of the history of DSS when it comes to understanding the problems they are trying to address. In this article, we argue that this gap in our understanding of the dynamics of DSS development must be addressed by the development of suitable analysis techniques that allow the capture of the l...

ICEIS 2009 and Springer-LNCS Vol.73 2011, 2011

"Evidence-Based Practice (EBP) represents a decision-making process centered on justifications of relevant information contained scientific research proof found in the Internet. Context is a type of knowledge that supports identifying what is or is not relevant in a given situation. Therefore, the integration of evidence and context is still an open issue. Besides, EBP procedures do not provide mechanisms to retain strategic knowledge from individual solutions, which could facilitate the learning of decision makers, preserving evidences used. On the other hand, Case-Based Reasoning (CBR) uses the history of similar cases and provides mechanisms to retain problem-solving. This paper proposes the integration of the CBR model with EBP procedures and Context to support decision making. Our approach includes a conceptual framework extended to support the development of applications that combines cases, evidence and context, preserving the characteristics of usability and portability across domains. An implementation in the area of crime prevention illustrates the usage of our proposal."

Group Decision and Negotiation, 2006

Decisions are frequently sent to implementers without the context that guided them. It should not be a surprise, then, that results are not as expected. The lack of supplementary information and a common context produces wrongly implemented or lost decisions. This paper proposes a solution to this problem based on groupware technology. In particular, a combination of tools including shared workspaces, process modeling with workflow and a discussion tool, is proposed. A case is used to illustrate the problem and its solution.

Many attempts have been made to capture, on the one hand, the nature of knowledge, and on the other hand, the nature of context. In this paper, we compare the two concepts of context and knowledge which, obviously, share some common aspects. Rather than trying to precisely define knowledge and context, we review the generally proposed characteristics of both concepts and while we conclude to a large overlapping of the two concepts, we also emphasize their differences as regards decision making and action.

The Florida AI Research Society Conference, 2004

This paper is an extension to and revision of Gonzalez and Ahlers' (6) definition of the Context-Based Reasoning Paradigm. Included are rigorous definitions of all terms and components applicable to CxBR models along with a discussion on how and where these models store and execute tactical knowledge. In addition, new terms and concepts are introduced that justify the need for

Proceedings of the First International and …, 1997

In this paper, using the framework of Multicriteria Decision Support Systems (MCDSSs), we try to identify what contextual knowledge is and where the contextual knowledge is necessary. The MCDSS framework is a good model to specify the exact role ...

Decision Support Systems (DSS) have a great role in assisting decision makers in many organizations to identify and solve problems in order to make decisions. In the area of database management, many approaches have been used to automate procedures set for complex activities such as performance and database recovery. However, procedures need to be contextualized in order to take into account the permanent changing of technical and social contextual elements added in DBA (Database Administrator) practices. This paper presents a context-based prototype for decision making to support experts in database management and administration. The prototype uses a software-modeling tool called Contextual Graphs (CxG).