Understandability is a key challenge in explanation provision and estimating well what users may already know can help offering better explanations.
Abstract. The research project MEDICO aims at developing an intelligent, robust and scalable semantic search engine for medical documents. The search engine of the MEDICO demonstrator RadSem is based on formal ontologies and is designated for different kinds of users, such as medical doctors, medical IT professionals, patients, and policy makers. Since semantic search results are not always self-explanatory, explanations are necessary to support requirements of different user groups. For this reason, an explanation facility is integrated into RadSem employing the same ontologies for explanation generation. In this work, we present a user experiment that evaluates the intelligibility of labels provided by the used ontologies with respect to different user groups. We discuss the results for refining our current approach for explanation generation in order to provide understandable justifications of semantic search results. Here, we focus on medical experts and laymen, respectively, using semantic networks as form of depiction.
[Björn Forcher, Kinga Schumacher, Michael Sintek, and Thomas Roth-Berghofer. Evaluating the intelligibility of medical ontological terms. In Joachim Baumeister and Grzegorz J. Nalepa, editors, Proceedings of the 5th Workshop on Knowledge Engineering and Software Engineering (KESE-2009), http://CEUR-WS.org/Vol-486/.]