Reconstructive expert system explanation
Artificial Intelligence
Explanation in second generation expert systems
Second generation expert systems
Knowledge-based system explanation: the ripple-down rules alternative
Knowledge and Information Systems
Patterns of semantic relations to improve image content search
Web Semantics: Science, Services and Agents on the World Wide Web
A Scalable Architecture for Cross-Modal Semantic Annotation and Retrieval
KI '08 Proceedings of the 31st annual German conference on Advances in Artificial Intelligence
RadSem: Semantic Annotation and Retrieval for Medical Images
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
Intrinsic plagiarism detection
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
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MEDICO aims to develop an intelligent, robust, and scalable semantic search engine for medical images. The search engine of the MEDICO demonstrator RadSem is based on formal ontologies and designated for different kinds of users such as medical doctors or patients. An explanation facility integrated into RadSem justifies search results by showing a connection between query and result. The constructed explanations are depicted as semantic networks containing various medical concepts and labels. This paper addresses the tailoring of justifications to different kinds of users regarding such quality aspects as understandability or amount of information. A user experiment shows that under certain conditions the quality of justifications can be pre-estimated by considering the usage frequency of medical terms in natural language.