In natural language, unlike formal logic, concepts are inherently flexible and graded. They give different degrees of importance to defining features, allow for different degrees of typicality, and permit a rich array of combination rules. Applications such as natural language processing and semantic search can greatly benefit from a richer representation of natural concepts to capture this flexibility. In this paper we introduce a new hierarchical representation of concepts inspired by Gardenfors’ work on conceptual spaces, which incorporates a probability model of prototypes to account for vague concept boundaries, semantic uncertainty and feature weights within concept ontologies.
- Conceptual spaces
- Concept combination