Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Exploiting hierarchical domain structure to compute similarity
ACM Transactions on Information Systems (TOIS)
A Logical Generalization of Formal Concept Analysis
ICCS '00 Proceedings of the Linguistic on Conceptual Structures: Logical Linguistic, and Computational Issues
Pattern Structures and Their Projections
ICCS '01 Proceedings of the 9th International Conference on Conceptual Structures: Broadening the Base
Extending Attribute Dependencies for Lattice-Based Querying and Navigation
ICCS '08 Proceedings of the 16th international conference on Conceptual Structures: Knowledge Visualization and Reasoning
BioRegistry: automatic extraction of metadata for biological database retrieval and discovery
Proceedings of the 10th International Conference on Information Integration and Web-based Applications & Services
Many-Valued Concept Lattices for Conceptual Clustering and Information Retrieval
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Querying a bioinformatic data sources registry with concept lattices
ICCS'05 Proceedings of the 13th international conference on Conceptual Structures: common Semantics for Sharing Knowledge
Backing composite web services using formal concept analysis
ICFCA'11 Proceedings of the 9th international conference on Formal concept analysis
Why and how knowledge discovery can be useful for solving problems with CBR
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
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In this paper we propose an approach which combines semantic resources and formal concept analysis to deal with heterogenous data sets represented as many-valued (MV) formal contexts. We define a new Galois connection considering the semantic relationships between attribute values in a MV context. The semantic relationships are used to calculate the similarity between attribute values to decide whether an attribute is shared by a set of objects or not. Then, based on this Galois connection, we define MV formal concepts and MV concept lattices. Depending on a chosen similarity threshold, MV concept lattices may have different levels of precision. We take advantage of this feature to browse the content of a biological databases repository in a dynamic and progressive way. The browsing process combines the navigation in several MV concept lattices and allows zooming operations by switching between MV concept lattices with higher or lower precision.