Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
Models of incremental concept formation
Machine learning: paradigms and methods
Incremental concept formation with composite objects
Proceedings of the sixth international workshop on Machine learning
Knowledge acquisition by methods of formal concept analysis
Proceedings of the conference on Data analysis, learning symbolic and numeric knowledge
Knowledge Acquisition Via Incremental Conceptual Clustering
Machine Learning
An approach to the classification of domain models in support of analogical reuse
SSR '95 Proceedings of the 1995 Symposium on Software reusability
Automatic inheritance hierarchy restructuring and method refactoring
Proceedings of the 11th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Journal of Systems and Software - Special issue on artificial and computational intelligence for decisions, control, and automation in engineering and industrial applications
A partition-based approach towards constructing Galois (concept) lattices
Discrete Mathematics
Computing iceberg concept lattices with TITANIC
Data & Knowledge Engineering
Formal Concept Analysis on Its Way from Mathematics to Computer Science
ICCS '02 Proceedings of the 10th International Conference on Conceptual Structures: Integration and Interfaces
Efficient Data Mining Based on Formal Concept Analysis
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Off to new shores: conceptual knowledge discovery and processing
International Journal of Human-Computer Studies
A multi-level conceptual data reduction approach based on the Lukasiewicz implication
Information Sciences: an International Journal - Special issue: Information technology
Ontology-based knowledge fusion framework using graph partitioning
IEA/AIE'2003 Proceedings of the 16th international conference on Developments in applied artificial intelligence
Information Sciences: an International Journal
Towards a machine learning approach based on incremental concept formation
Intelligent Data Analysis
Discovering shared conceptualizations in folksonomies
Web Semantics: Science, Services and Agents on the World Wide Web
Concept analysis via rough set and AFS algebra
Information Sciences: an International Journal
A new model of evaluating concept similarity
Knowledge-Based Systems
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Fusion of Claude Bernard's Experiments for Scientific Discovery Reasoning
ICCS '09 Proceedings of the 17th International Conference on Conceptual Structures: Conceptual Structures: Leveraging Semantic Technologies
Abstraction of objects by conceptual clustering
Information Sciences: an International Journal
Performances of galois sub-hierarchy-building algorithms
ICFCA'07 Proceedings of the 5th international conference on Formal concept analysis
Improving the reuse possibilities of the behavioral aspects of object-oriented domain models
ER'00 Proceedings of the 19th international conference on Conceptual modeling
Introducing semantic knowledge in high-level fusion
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
A new algebraic structure for formal concept analysis
Information Sciences: an International Journal
Journal of Intelligent Information Systems
Concept lattice and AFS algebra
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Formal concept mining: a statistic-based approach for pertinent concept lattice construction
ASIAN'04 Proceedings of the 9th Asian Computing Science conference on Advances in Computer Science: dedicated to Jean-Louis Lassez on the Occasion of His 5th Cycle Birthday
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An important structuring mechanism for knowledge bases is building an inheritance hierarchy of classes based on the content of their knowledge objects. This hierarchy facilitates group-related processing tasks such as answering set queries, discriminating between objects, finding similarities among objects, etc. Building this hierarchy is a difficult task for the knowledge engineer. Conceptual clustering may be used to automate or assist the engineer in the creation of such a classification structure. This article introduces a new conceptual clustering method which addresses the problem of clustering large amounts of structured objects. The conditions under which the method is applicable are discussed.