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

Using Data Crawlers and Semantic Web to Build Financial XBRL Data Generators: The SONAR Extension Approach

“…The Ontology Population system [ 51 ] is capable of gathering knowledge from semi-structured and nonstructured texts. The ultimate goal of our approach is to populate an ontology with all the relevant information identified.…”