Dynamic faceted navigation in decision making using Semantic Web technology

Abstract Categorization in the decision making classifies decision makers' experiences about the world and provides a guide to reach a goal. This implies that dynamically providing categories reflecting the given decision context gives a great enhancement in decision quality. This study discusses the dynamic category selection under the Semantic Web environment, focusing on an implementation of a decision support system, the dynamic facet navigation system working with an ontology. Predefined fixed categories are provided to refine search results to evade use of complex queries and tedious review of search results, but they often output insensible information because of never reflecting the difference in search results. This paper proposes a dynamic category selection mechanism by using the total gain ratio under a given ontology, and a reordering scheme for resulted categories. It proves the validity of the proposed approach with a statistical analysis lastly.

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