Applied multivariate analysis
A functional approach to integrating database and expert systems
Communications of the ACM
Artificial Intelligence and the Design of Expert Systems
Artificial Intelligence and the Design of Expert Systems
Conceptual Data Modeling of Expert Systems
IEEE Expert: Intelligent Systems and Their Applications
KADBASE: Interfacing Expert Systems with Databases
IEEE Expert: Intelligent Systems and Their Applications
Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley series in artificial intelligence)
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A methodology for determining remains identification (ID) following a mass disaster is presented. The solution methodology is domain-independent and capable of addressing a wide range of assignment problems. A knowledge-based fatal incident decision model (FINDM) for providing a decision support to forensic scientists involved in the skeletal ID process is discussed. A mathematical framework for FINDM is developed that integrates a knowledge base with a network flow algorithm for resolving conflicts during the ID process. The FINDM framework has been implemented can an IBM PC and includes an observation advisor, an assignment advisor, and a conflict resolution module. Knowledge acquisition and representation issues are discussed, along with a numerical example and results. With respect to the remains ID problem, the FINDM approach shifts major efforts in resolving the problem from that of establishing a method of assignment to that of controlling the quality of data collected, improving domain knowledge, and analyzing conflicts.