Decision Support Using Causation Knowledge Base

• Published in: IEEE transactions on systems, man, and cybernetics man, and cybernetics, 1982-01, Vol.12 (6), p.765-777
• Main Authors: Nakamura, Kiyohiko, Iwai, Sosuke, Sawaragi, Tetsuo
• Format: Article
• Language: English
• Subjects: Automation; Collaborative software; Data mining; Decision support systems; Environmental economics; Hardware; Information retrieval; Knowledge representation; Skeleton
• ISSN: 0018-9472; 2168-2909
• DOI: 10.1109/TSMC.1982.4308910

A decision support system using a knowledge base of documentary data is presented. Causal assertions in documents are extracted and organized into cognitive maps, which are networks of causal relations, by the methodology of documentary coding. Our knowledge base is constructed by joining cognitive maps of several documents concerned with a societal complex problem. The knowledge base is an integration of several expertises described in documents, though it is only concerned with causal structure of the problem, and includes overall and detailed information about the problem. Decisionmakers concerned with the problem interactively retrieve relevant information from the knowledge base in the process of decisionmaking and form their overall and detailed understanding of the complex problem based on the expertises stored in the knowledge base. Three retrieval modes are proposed according to types of the decisionmakers' requests: 1) skeleton maps indicate overall causal structure of the problem, 2) hierarchical graphs give detailed information about parts of the causal structure, and 3) sources of causal relations are presented when necessary, for example when the decisionmaker wants to browse the causal assertions in documents. An illustrative example is presented to show how our knowledge base system assists the decisionmaker in grasping the complex problem in its totality. In addition two coders' coding results of a document are investigated under the same condition and confirm the reliability of the methodology for coding cognitive maps, i.e., the capacity of the method to yield the same coding result.