Principled design of the modern Web architecture
ACM Transactions on Internet Technology (TOIT)
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Ontology Learning for the Semantic Web
IEEE Intelligent Systems
Jena: implementing the semantic web recommendations
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Concept similarity in Formal Concept Analysis: An information content approach
Knowledge-Based Systems
Learning concept hierarchies from text corpora using formal concept analysis
Journal of Artificial Intelligence Research
Formal concept analysis in information science
Annual Review of Information Science and Technology
Lexico-logical acquisition of OWL DL axioms: an integrated approach to ontology refinement
ICFCA'08 Proceedings of the 6th international conference on Formal concept analysis
Comparing and analyzing the computational complexity of FCA algorithms
SAICSIT '10 Proceedings of the 2010 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists
Extracting relevant questions to an RDF dataset using formal concept analysis
Proceedings of the sixth international conference on Knowledge capture
In-close2, a high performance formal concept miner
ICCS'11 Proceedings of the 19th international conference on Conceptual structures for discovering knowledge
Conceptual navigation in RDF graphs with SPARQL-Like queries
ICFCA'10 Proceedings of the 8th international conference on Formal Concept Analysis
Query-based multicontexts for knowledge base browsing: an evaluation
ICCS'06 Proceedings of the 14th international conference on Conceptual Structures: inspiration and Application
Review: Formal concept analysis in knowledge processing: A survey on applications
Expert Systems with Applications: An International Journal
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Semantic Web efforts aim to bring the WWW to a state in which all its content can be interpreted by machines; the ultimate goal being a machine-processable Web of Knowledge. We strongly believe that adding a mechanism to extract and compute concepts from the Semantic Web will help to achieve this vision. However, there are a number of open questions that need to be answered first. In this paper we will establish partial answers to the following questions: 1) Is it feasible to obtain data from the Web (instantaneously) and compute formal concepts without a considerable overhead; 2) have data sets, found on the Web, distinct properties and, if so, how do these properties affect the performance of concept discovery algorithms; and 3) do state-of-the-art concept discovery algorithms scale wrt. the number of data objects found on the Web?