Information extraction and text summarization using linguistic knowledge acquisition
Information Processing and Management: an International Journal
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International Journal of Human-Computer Studies - Special issue: object-oriented approaches in artificial intelligence and human-computer interaction
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AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
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Artificial Intelligence - Special volume on empirical methods
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Bagging and boosting a treebank parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
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NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
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EACL '95 Proceedings of the seventh conference on European chapter of the Association for Computational Linguistics
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COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
A text understander that learns
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Using decision trees to construct a practical parser
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Morphological rule induction for terminology acquistion
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Experiments in automated lexicon building for text searching
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
An overview of methods and tools for ontology learning from texts
The Knowledge Engineering Review
Survey on ontology learning from Web and open issues
ISIICT'09 Proceedings of the Third international conference on Innovation and Information and Communication Technology
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We introduce a methodology for automating the maintenance and growth of domain-specific concept taxonomies and grammatical class hierarchies simultaneously, based on knowledge capture from natural language texts. The assimilation process is centered around the linguistic and conceptual `quality' of various forms of evidence underlying the generation, assessment and on-going refinement of lexical and concept hypotheses. On the basis of the strength of evidence, hypotheses are ranked according to plausibility, and the most reasonable ones are selected for assimilation into the given lexical class hierarchy and domain ontology.