ABSTRACT
A semantics-based DSS can solve most of the problems associated with a plain DSS. This chapter focuses on best practices—i.e., decision trees, ontological representation, case-based and rule-based reasoning—and demonstrates an ontology-supported hybrid reasoning framework for generating advice. As in the previous chapter, an emergency domain—in this case earthquakes—has been chosen to demonstrate the applicability of the integrated approach. A case base of past earthquakes is created with ontological representation and recommendations generated by its real-time synthesis and matching with the input earthquake data using decision-tree classification. The rule base serves as expert advice in case of a similarity mismatch with all historical cases. This framework generates recommendations with proper justification based on past experiences and experts’ codified knowledge. It can support decision makers and emergency managers by providing an overview of the current situation and generating a rapid automated action plan within a time constraint, which can be further validated by an expert. The system has been tested on the domain of earthquakes and can work for any emergency situation whose domain knowledge is entered into it.
