Incremental learning of concept descriptions: A method and experimental results
Machine intelligence 11
Using difunctional relations in information organization
Information Sciences—Applications: An International Journal
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A partition-based approach towards constructing Galois (concept) lattices
Discrete Mathematics
Foundations of Algorithms Using Java Pseudocode
Foundations of Algorithms Using Java Pseudocode
RelMiCS '09/AKA '09 Proceedings of the 11th International Conference on Relational Methods in Computer Science and 6th International Conference on Applications of Kleene Algebra: Relations and Kleene Algebra in Computer Science
A Method for Building Concept Lattice Based on Matrix Operation
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Computing intensions of digital library collections
ICFCA'07 Proceedings of the 5th international conference on Formal concept analysis
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Information resources in today's cyber communities over the World Wide Web are increasingly growing in size with an ever increasing pace of change. As information demand increases, more knowledge management and retrieval applications need to exhibit a degree of resilience towards information change, and must be able to handle incremental changes in a reasonable time. In this paper we are defining a new system that utilizes new conceptual methods using the notion of pseudo maximal rectangles (i.e. the union of all non enlargeable rectangles containing a pair (a,b) of a binary relation) for managing incremental information organization and structuring in a dynamic environment. The research work in hand focuses on managing changes in an information store relevant to a specific domain of knowledge attempted through addition and deletion of information. The incremental methods developed in this work should support scalability in change-prone information stores and be capable of producing updates to end users in an efficient time. The paper will also discuss some algorithmic aspects and evaluation results concerning the new methods.