Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
A logic-based calculus of events
New Generation Computing
A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Building a large-scale knowledge base for machine translation
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Qualitative probabilities for default reasoning, belief revision, and causal modeling
Artificial Intelligence
Knowledge engineering: principles and methods
Data & Knowledge Engineering - Special jubilee issue: DKE 25
Knowledge representation: logical, philosophical and computational foundations
Knowledge representation: logical, philosophical and computational foundations
On the representation of roles in object-oriented and conceptual modelling
Data & Knowledge Engineering
An enriched knowledge model for formal ontological analysis
Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001
Supporting ontological analysis of taxonomic relationships
Data & Knowledge Engineering - ER2000
Building a Chemical Ontology Using Methontology and the Ontology Design Environment
IEEE Intelligent Systems
Conceptual Modeling for Distributed Ontology Environments
ICCS '00 Proceedings of the Linguistic on Conceptual Structures: Logical Linguistic, and Computational Issues
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Formal ontological analysis is a methodology that uses ideas from philosophy in order to guide the process of building ontologies with a correct and as untangled a structure as possible.This paper presents an ontology model that aims to facilitate formal ontological analysis, by providing a set of meta-properties which characterise the behaviour of concept properties in a concept definition, to provide a richer semantics of the concept. We describe concepts in terms of their attributes (characterising features) and we also describe the role played by these features in the concept definition: whether they are prototypical or exceptional; whether they are permitted to change over time, and if so, how often this happens; how likely is a concept to show these features, etc. We show that these meta-properties, besides enriching concept descriptions, can be used to determine whether the notions of identity and rigidity hold, thus supporting in part the OntoClean [31] methodology.