2019
AAAI
AAAI 2019
Relaxing and Restraining Queries for OBDA
Abstract
Abstract We advocate the use of ontologies for relaxing and restraining queries, so that they retrieve either more or less answers, enabling the exploration of a given dataset. We propose a set of rewriting rules to relax and restrain conjunctive queries (CQs) over datasets mediated by an ontology written in a dialect of DL-Lite with complex role inclusions (CRIs). The addition of CRI enables the representation of knowledge about data involving ordered hierarchies of categories, in the style of multi-dimensional data models. Although CRIs in general destroy the first-order rewritability of CQs, we identify settings in which CQs remain rewritable.
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Conference Pioneer
— AAAI 2019
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Interdisciplinary Bridge
— Artificial Intelligence and Computer Science and Knowledge & Reasoning and Machine Learning
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Trend Setter
— Ontology Learning
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Optimization & Theory > Theory
Knowledge & Reasoning > Representation > Knowledge Representation
Knowledge & Reasoning > Representation > Ontology Learning
Knowledge & Reasoning > Reasoning > Automated Reasoning
Computer Science > Foundations > Formal Languages
Artificial Intelligence > Core AI > Knowledge Representation