Learning and reasoning by analogy
Communications of the ACM
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Fuzzy Relational Systems: Foundations and Principles
Fuzzy Relational Systems: Foundations and Principles
Ontology Learning for the Semantic Web
IEEE Intelligent Systems
Logical Scaling in Formal Concept Analysis
ICCS '97 Proceedings of the Fifth International Conference on Conceptual Structures: Fulfilling Peirce's Dream
Ontology Learning by Clustering Based on Fuzzy Formal Concept Analysis
COMPSAC '07 Proceedings of the 31st Annual International Computer Software and Applications Conference - Volume 01
Interval-Valued Fuzzy Formal Concept Analysis
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
A New Method for Fuzzy Formal Concept Analysis
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Formal concept analysis in information science
Annual Review of Information Science and Technology
Towards an automatic fuzzy ontology generation
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
mTRACK: monitoring time-varying relations in approximately
CISDA'09 Proceedings of the Second IEEE international conference on Computational intelligence for security and defense applications
Ontology-based fuzzy retrieval for digital library
ICADL'07 Proceedings of the 10th international conference on Asian digital libraries: looking back 10 years and forging new frontiers
Computing the lattice of all fixpoints of a fuzzy closure operator
IEEE Transactions on Fuzzy Systems - Special section on computing with words
Discovery of time-varying relations using fuzzy formal concept analysis and associations
International Journal of Intelligent Systems - New Trends for Ontology-Based Knowledge Discovery
Parallel algorithm for computing fixpoints of Galois connections
Annals of Mathematics and Artificial Intelligence
Crisply generated fuzzy concepts
ICFCA'05 Proceedings of the Third international conference on Formal Concept Analysis
Hi-index | 0.00 |
Creative knowledge discovery—finding useful, previously unknown links between concepts—is a vital tool in unlocking the economic and social value of the vast range of networked data and services that is now available. We define “standard” knowledge discovery as the search for explanatory and predictive patterns in a specific domain, usually with a large volume of data. In contrast, creative knowledge discovery is concerned with the creation of new (and effective) patterns—either by generalization of existing patterns or by analogy to patterns in other domains. An important precondition for creative knowledge discovery is that we understand the relations within the data. Fuzzy formal concept analysis is a powerful approach that enables us to find embedded structure in data and to extract novel concepts that can be used in subsequent processing such as creative knowledge discovery. This paper outlines a fast algorithm for computing fuzzy formal concepts and provides a brief illustration of the use of fuzzy formal concept analysis in creative knowledge discovery. © 2013 Wiley Periodicals, Inc.