Populating Knowledge Based Decision Support Systems

Abstract

Knowledge-based decision support systems (KBDSS) hold up business and organizational decision-making activities on the basis of the knowledge available concerning the domain under question. One of the main problems with knowledge bases is that their construction is a time-consuming task. A number of methodologies have been proposed in the context of the Semantic Web to assist in the development of ontology-based knowledge bases. In this paper, we present a technique for populating knowledge bases from semi-structured text which take advantage of the semantic underpinnings provided by ontologies. This technique has been tested and evaluated in the financial domain

SINVLIO: Using semantics and fuzzy logic to provide individual investment portfolio recommendations

“…[23], [22]). Financial Ontologies like FEF ontology [42] or the ontology of the SONAR project [25] have been applied to categorize and recommend financial products. However, ontologies regarding the psycho-social aspects of investors have not been found in the research work carried out so far.…”