Combinatorial search
Terminological reasoning is inherently intractable (research note)
Artificial Intelligence
LaSSIE: a knowledge-based software information system
Communications of the ACM - Special issue on software engineering
Subsumption in KL-ONE is undecidable
Proceedings of the first international conference on Principles of knowledge representation and reasoning
KRIS: Knowledge Representation and Inference System
ACM SIGART Bulletin - Special issue on implemented knowledge representation and reasoning systems
ACM SIGART Bulletin - Special issue on implemented knowledge representation and reasoning systems
Inside the LOOM description classifier
ACM SIGART Bulletin - Special issue on implemented knowledge representation and reasoning systems
The CLASSIC knowledge representation system: guiding principles and implementation rationale
ACM SIGART Bulletin - Special issue on implemented knowledge representation and reasoning systems
ACM SIGART Bulletin - Special issue on implemented knowledge representation and reasoning systems
Enabling technology for knowledge sharing
AI Magazine
The complexity of existential quantification in concept languages
Artificial Intelligence
Configuration as a Consistency Maintenance Task
Künstliche Intelligenz, GWAI-88, 12. Jahrestagung
International Workshop on Terminological Logics - Proceedings
International Workshop on Terminological Logics - Proceedings
Predicting reasoning performance using ontology metrics
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
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The family of terminological representation systems has its roots in the representation system KLONE. Since the development of this system more than a dozen similar representation systems have been developed by various research groups. These systems vary along a number of dimensions. In this paper, we present the results of an empirical analysis of six such systems. Surprisingly, the systems turned out to be quite diverse leading to problems when transporting knowledge bases from one system to another. Additionally, the runtime performance between different systems and knowledge bases varied more than we expected. Finally, our empirical runtime performance results give an idea of what runtime performance to expect from such representation systems. These findings complement previously reported analytical results about the computational complexity of reasoning in such systems.