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Formalization of weighted factors analysis

Hessami, A; Hunter, A; (2002) Formalization of weighted factors analysis. KNOWL-BASED SYST , 15 (7) 377 - 390.

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Weighted Factors Analysis (WcFA) has been proposed as a new approach for elicitation, representation, and manipulation of knowledge about a given problem, generally at a high and strategic level. Central to this proposal is that a group of experts in the area of the problem can identify a hierarchy of factors with positive or negative influences on the problem outcome. The tangible output of WeFA is a directed weighted graph called a WcFA graph. This is a set of nodes denoting factors that can directly or indirectly influence an overall aim of the graph. The aim is also represented by a node. Each directed arc is a direct influence of one factor on another. A chain of directed arcs indicates an indirect influence. The influences may be identified as either positive or negative. For example, sales and costs are two factors that influence the aim of profitability in an organization. sales has a positive influence on profitability and costs has a negative influence on profitability. In addition, the relative significance of each influence is represented by a weight. In this paper, we develop Binary WeFA which is a variant of WeFA where the factors in the graph are restricted to being either true or false. Imposing this restriction on a WeFA graph allows us to be more precise about the meaning of the graph and of reasoning in it. Binary WeFA is a new proposal that provides a formal yet sufficiently simple language for logic-based argumentation for use by business people in decision-support and knowledge management. Whilst Binary WcFA is expressively simpler than other logic-based argumentation formalisms, it does incorporate a novel formalization of the notion of significance. (C) 2002 Elsevier Science B.V. All rights reserved.

Type: Article
Title: Formalization of weighted factors analysis
Keywords: argumentation, knowledge representation and reasoning, logic, decision-support, scenario analysis, knowledge management
URI: http://discovery.ucl.ac.uk/id/eprint/105528
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