Fast qualitative reasoning about categories in conceptual spaces

Authors:
Ickjai Lee
Affiliations:
School of Information Technology, James Cook University, Douglas Campus, Townsville, QLD 4811, Australia
Venue:
Design and application of hybrid intelligent systems
Year:
2003

Citing 6
Cited 2

Spatial tessellations: concepts and applications of Voronoi diagrams

Spatial tessellations: concepts and applications of Voronoi diagrams
Computer science as empirical inquiry: symbols and search

Communications of the ACM
Conceptual Spaces: The Geometry of Thought

Conceptual Spaces: The Geometry of Thought
Qualitative Spatial Representation and Reasoning with the Region Connection Calculus

Geoinformatica
GIS: A Computing Perspective, 2nd Edition

GIS: A Computing Perspective, 2nd Edition
Multi-level clustering and reasoning about its clusters using region connection calculus

PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining

AN ORDER-k VORONOI APPROACH TO GEOSPATIAL CONCEPT MANAGEMENT WITHIN CONCEPTUAL SPACES

Applied Artificial Intelligence
Data mining coupled conceptual spaces for intelligent agents in data-rich environments

KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV

Quantified Score

Hi-index	0.00

Visualization

Abstract

Categorization is a central task in cognitive science and artificial intelligence. Efficient reasoning about categories is becoming of great importance as intelligent agents are required to perform complex tasks in data-rich environments. Gärdenfors and Williams [6] introduce a robust framework for categorization and reasoning about categories within conceptual spaces. This paper extends their work and presents a number of efficient reasoning properties that greatly reduce the search space resulting in fast derivation of reasoning about categories.