Learning Information Extraction Rules for Semi-Structured and Free Text
Machine Learning - Special issue on natural language learning
Relational learning of pattern-match rules for information extraction
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Learning pattern rules for Chinese named entity extraction
Eighteenth national conference on Artificial intelligence
A maximum entropy approach to information extraction from semi-structured and free text
Eighteenth national conference on Artificial intelligence
Relational learning techniques for natural language information extraction
Relational learning techniques for natural language information extraction
Named entity recognition: a maximum entropy approach using global information
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Closing the gap: learning-based information extraction rivaling knowledge-engineering methods
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Adaptive information extraction from text by rule induction and generalisation
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
CRYSTAL inducing a conceptual dictionary
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
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The World Wide Web's vast growth contains a great variety and quantity of on-line information. People need to have the computing systems with the ability to process those documents to simplify the text information. One type of appropriate processing is called Information Extraction (IE) technology. Information extraction can be regarded as one kind of classification problems and one of the main methods to deal with the problem is pattern rule induction. Due to the uncertainty during the induction of pattern rules from natural language texts, in this paper we introduce a Fuzzy pattern Rule Induction System (FRIS) to obtain fuzzy pattern rules for information extraction from semi-structured webpages and free texts.