2010 UnsupervisedOntologyInductionfr
- (Poon et al., 2010) ⇒ Hoifung Poon, and Pedro Domingos. (2010). “Unsupervised Ontology Induction from Text.” In: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics.
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Cited By
- http://scholar.google.com/scholar?q=%22Unsupervised+ontology+induction+from+text%22+2010
- http://dl.acm.org/citation.cfm?id=1858681.1858712&preflayout=flat#citedby
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Abstract
Extracting knowledge from unstructured text is a long-standing goal of NLP. Although learning approaches to many of its subtasks have been developed (e.g., parsing, taxonomy induction, information extraction), all end-to-end solutions to date require heavy supervision and/or manual engineering, limiting their scope and scalability. We present OntoUSP, a system that induces and populates a probabilistic ontology using only dependency-parsed text as input. OntoUSP builds on the USP unsupervised semantic parser by jointly forming ISA and IS-PART hierarchies of lambda-form clusters. The ISA hierarchy allows more general knowledge to be learned, and the use of smoothing for parameter estimation. We evaluate OntoUSP by using it to extract a knowledge base from biomedical abstracts and answer questions. OntoUSP improves on the recall of USP by 47% and greatly outperforms previous state-of-the-art approaches.
References
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Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
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2010 UnsupervisedOntologyInductionfr | Pedro Domingos Hoifung Poon | Unsupervised Ontology Induction from Text |