Learning regular sets from queries and counterexamples
Information and Computation
Efficient learning of context-free grammars from positive structural examples
Information and Computation
Inference of finite automata using homing sequences
Information and Computation
Knowledge representation: logical, philosophical and computational foundations
Knowledge representation: logical, philosophical and computational foundations
Inference of Reversible Languages
Journal of the ACM (JACM)
Ontology Learning for the Semantic Web
Ontology Learning for the Semantic Web
A brief survey of web data extraction tools
ACM SIGMOD Record
Machine Learning
Machine Learning
GA-based Learning of Context-Free Grammars using Tabular Representations
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce
Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce
Ontological Engineering
Automatic information extraction from large websites
Journal of the ACM (JACM)
Efficient Techniques for Effective Wrapper Induction
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
An automatic data grabber for large web sites
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
EPIA'05 Proceedings of the 12th Portuguese conference on Progress in Artificial Intelligence
Learning DFA from correction and equivalence queries
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
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Information produced by people usually has an implicit agreed-upon structure. However, this structure is not usually available to computer programs, where it could be used, for example, to aid in answering search queries. For example, when considering technical articles, one could ask for the occurrence of a keyword in a particular part of the article, such as the reference section. This implicit structure could be used, in the form of an ontology, to further the efforts of improving search in the semantic web. We propose a method to build ontologies encoding this structure information by the application of grammar inference techniques. This results in a semi-automatic approach to the inference of such ontologies. Our approach has two main components: (1) the inference of a grammatical description of the implicit structure of the supplied examples, and (2) the transformation of that description into an ontology. We present the application of the method to the inference of an ontology describing the structure of technical articles.