Elementary formal system as a unifying framework for language learning
COLT '89 Proceedings of the second annual workshop on Computational learning theory
Learning elementary formal systems
Theoretical Computer Science
Rich classes inferable from positive data
Information and Computation
Foundations of logic programming
Principles of knowledge representation
Learning Information Extraction Rules for Semi-Structured and Free Text
Machine Learning - Special issue on natural language learning
Polynomial-time learning of elementary formal systems
New Generation Computing
Inductive Inference: Theory and Methods
ACM Computing Surveys (CSUR)
Logic Programs for Intelligent Web Search
ISMIS '99 Proceedings of the 11th International Symposium on Foundations of Intelligent Systems
A Guided Tour Across the Boundaries of Learning Recursive Languages
Algorithmic Learning for Knowledge-Based Systems, GOSLER Final Report
Wrapper induction for information extraction
Wrapper induction for information extraction
Formal languages and their relation to automata
Formal languages and their relation to automata
Extending Elementary Formal Systems
ALT '01 Proceedings of the 12th International Conference on Algorithmic Learning Theory
Consistency Queries in Information Extraction
ALT '02 Proceedings of the 13th International Conference on Algorithmic Learning Theory
Mining Semi-structured Data by Path Expressions
DS '01 Proceedings of the 4th International Conference on Discovery Science
Clipping and Analyzing News Using Machine Learning Techniques
DS '01 Proceedings of the 4th International Conference on Discovery Science
Modelling Semi-structured Documents with Hedges for Deduction and Induction
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
Knowledge federation over the web based on meme media technologies
Proceedings of the 2005 international conference on Federation over the Web
Mechanisms of knowledge evolution for web information extraction
Proceedings of the 2005 international conference on Federation over the Web
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The number, the size, and the dynamics of Internet information sources bears abundant evidence of the need for automation in information extraction. This calls for representation formalisms that match the World Wide Web reality and for learning approaches and learnability results that apply to these formalisms. The concept of elementary formal systems is appropriately generalized to allow for the representation of wrapper classes which are relevant to the description of Internet sources in HTML format. Related learning results prove that those wrappers are automatically learnable from examples. This is setting the stage for information extraction from the Internet by exploitation of inductive learning techniques.