Performance Heterogeneity and Approximate Reasoning in Description Logic Ontologies

  title={Performance Heterogeneity and Approximate Reasoning in Description Logic Ontologies},
  author={Rafael S Gonçalves and B. Parsia and U. Sattler},
  booktitle={International Semantic Web Conference},
  • Rafael S Gonçalves, B. Parsia, U. Sattler
  • Published in
    International Semantic Web…
  • Computer Science
  • Due to the high worst case complexity of the core reasoning problem for the expressive profiles of OWL 2, ontology engineers are often surprised and confused by the performance behaviour of reasoners on their ontologies. Even very experienced modellers with a sophisticated grasp of reasoning algorithms do not have a good mental model of reasoner performance behaviour. Seemingly innocuous changes to an OWL ontology can degrade classification time from instantaneous to too long to wait for… CONTINUE READING
    50 Citations
    How Long Will It Take? Accurate Prediction of Ontology Reasoning Performance
    • 23
    • Highly Influenced
    • PDF
    What Makes Ontology Reasoning so Arduous?: Unveiling the key ontological features
    • 12
    Towards Unveiling the Ontology Key Features Altering Reasoner Performances
    • 7
    • PDF
    ComR: a combined OWL reasoner for ontology classification
    • 1
    Module-based classification of OWL ontologies
    • 4
    Predicting the Empirical Robustness of the Ontology Reasoners based on Machine Learning Techniques
    • 4
    • PDF
    Consequence-based reasoning for ontology classification
    • 4
    • PDF


    JustBench: A Framework for OWL Benchmarking
    • 28
    • PDF
    Modular Reuse of Ontologies: Theory and Practice
    • 399
    • PDF
    Soundness Preserving Approximation for TBox Reasoning
    • 86
    • Highly Influential
    • PDF
    What Is Approximate Reasoning?
    • 46
    • PDF
    HermiT: A Highly-Efficient OWL Reasoner
    • 457
    • PDF
    The Modular Structure of an Ontology: Atomic Decomposition
    • 97
    • PDF
    Tractable Reasoning via Approximation
    • 207
    FaCT++ Description Logic Reasoner: System Description
    • 1,133
    • PDF
    Ontology Performance Profiling and Model Examination: First Steps
    • 27
    • PDF
    CEL - A Polynomial-Time Reasoner for Life Science Ontologies
    • 234
    • PDF