Intuitive Justifications of Medical Semantic Search Results

Björn Forcher, Thomas Roth-Berghofer, Stefan Agne, Andreas Dengel

In: International Journal Engineering Applications of Artificial Intelligence (EAAI) 39 Pages 1-17 Elsevier 2014.


To some extent, explanations in computer science are answers to questions. Often an explanatory dialogue is necessary to satisfy needs of software users. In this paper, we introduce the concept of intuitive explanation representing the first explanations in an explanatory dialogue. This kind of explanation does not require a situational context to be established or that there is a user model. Depending on an abstract model of explanation generation we present the generic explanation component Kalliope applying Semantic Technologies to construct intuitive explanations. We illustrate our generation approach by means of the semantic search engine KOIOS++ enabling keyword-based search on medical articles. Since semantic search results are often hard to understand Kalliope was integrated into KOIOS++ in order to justify search results. In this work we describe in detail the construction of intuitive explanations for inexperienced users in the medical domain building on the concepts of Semantic Frequency Classes and Semantic Cooccurrence Classes. Various user experiments illustrate that these concepts enable the explanation component to rate the understandability of labels and of label connections. We show how Kalliope exploits these valuations to construct and select understandable explanations.


German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz