A logical framework for depiction and image interpretation
Artificial Intelligence
Artificial Intelligence - Special volume on natural language processing
Construction of the L-fuzzy concept lattice
Fuzzy Sets and Systems
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
Information Retrieval
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Ontology Learning for the Semantic Web
IEEE Intelligent Systems
Magpie: supporting browsing and navigation on the semantic web
Proceedings of the 9th international conference on Intelligent user interfaces
Survey of semantic annotation platforms
Proceedings of the 2005 ACM symposium on Applied computing
A formal concept analysis approach for web usage mining
Intelligent information processing II
An algorithm based on counterfactuals for concept learning in the Semantic Web
Applied Intelligence
MyMap: Generating personalized tourist descriptions
Applied Intelligence
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
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
Towards a Media Interpretation Framework for the Semantic Web
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
Ontology Learning from Text Using Relational Concept Analysis
MCETECH '08 Proceedings of the 2008 International MCETECH Conference on e-Technologies
Lindig's Algorithm for Concept Lattices over Graded Attributes
MDAI '07 Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence
Learning concept hierarchies from text corpora using formal concept analysis
Journal of Artificial Intelligence Research
Towards an automatic fuzzy ontology generation
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
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
Logical formalization of multimedia interpretation
Knowledge-driven multimedia information extraction and ontology evolution
A template-based markup tool for semantic web content
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Hierarchical web resources retrieval by exploiting Fuzzy Formal Concept Analysis
Information Processing and Management: an International Journal
Learning to adapt cross language information extraction wrapper
Applied Intelligence
Bringing context-aware access to the web through spoken interaction
Applied Intelligence
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Semantic annotation is at the core of Semantic Web technology: it bridges the gap between legacy non-semantic web resource descriptions and their elicited, formally specified conceptualization, converting syntactic structures into knowledge structures, i.e., ontologies. Most existing approaches and tools are designed to deal with manual or semi-/automatic semantic annotation that exploits available ontologies through the pattern-based discovery of concepts. This work aims to generate the automatic semantic annotation of web resources, without any prefixed ontological support. The novelty of our approach is that, starting from web resources, content with a high-level of abstraction is obtained: concepts, connections between concepts, and instance-population are identified and arranged into an ex-novo ontology. The framework is designed to process resources from different sources (textual information, images, etc.) and generate an ontology-based annotation. A data-driven analysis reveals the data and their intrinsic relationships (in the form of triples) extracted from the resource content. On the basis of the discovered semantics, corresponding concepts and properties are modeled, allowing an ad hoc ontology to be built through an OWL-based coding annotation. The benefit of this approach is the generation of knowledge structured in a quite automatic way (i.e., the human support is restricted to the configuration of some parameters). The approach exploits a fuzzy extension of the mathematical modeling of Formal Concept Analysis and Relational Concept Analysis to generate the ontological structure of data resources.