The Complexity of Concept Languages

Abstract

ur K ¨ unstliche In-telligenz, DFKI) with sites in Kaiserslautern and Saarbrücken is a non-profit organization which was founded in 1988. The DFKI conducts application-oriented basic research in the field of artificial intelligence and other related subfields of computer science. The overall goal is to construct systems with technical knowledge and common sense which-by using AI methods-implement a problem solution for a selected application area. Currently, there are the following research areas at the DFKI: The DFKI strives at making its research results available to the scientific community. There exist many contacts to domestic and foreign research institutions, both in academy and industry. The DFKI hosts technology transfer workshops for shareholders and other interested groups in order to inform about the current state of research. From its beginning, the DFKI has provided an attractive working environment for AI researchers from Germany and from all over the world. The goal is to have a staff of about 100 researchers at the end of the building-up phase. c Deutsches Forschungszentrum für K ¨ unstliche Intelligenz 1995 This work may not be copied or reproduced in whole of part for any commercial purpose. Permission to copy in whole or part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of the Deutsche Forschungszen-trum für K ¨ unstliche Intelligenz, Kaiserslautern, Federal Republic of Germany; an acknowledgement of the authors and individual contributors to the work; all applicable portions of this copyright notice. Copying, reproducing, or republishing for any other purpose shall require a licence with payment of fee to Deutsches Forschungszentrum für K ¨ unstliche Intelligenz. Abstract The basic feature of Terminological Knowledge Representation Systems is to represent knowledge by means of taxonomies, here called terminologies, and to provide a specialized reasoning engine to do inferences on these structures. The taxonomy is built through a representation language called concept language (or description logic), which is given well-deened set-theoretic semantics. The ee-ciency of reasoning has often been advocated as a primary motivation for the use of such systems. Deduction methods and computational properties of reasoning problems in concept languages are the subject of this paper. The main contributions of the paper are: (1) a complexity analysis of concept satissability and subsumption for a wide class of concept languages; (2) the algorithms for these …

DOI: 10.1006/inco.1997.2625

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@inproceedings{Donini1991TheCO, title={The Complexity of Concept Languages}, author={Francesco M. Donini and Maurizio Lenzerini and Daniele Nardi and Werner Nutt}, booktitle={KR}, year={1991} }