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LREC
2010

Improving Domain-specific Entity Recognition with Automatic Term Recognition and Feature Extraction

13 years 5 months ago
Improving Domain-specific Entity Recognition with Automatic Term Recognition and Feature Extraction
Domain specific entity recognition often relies on domain-specific knowledge to improve system performance. However, such knowledge often suffers from limited domain portability and is expensive to build and maintain. Therefore, obtaining it in a generic and unsupervised manner would be a desirable feature for domain-specific entity recognition systems. In this paper, we introduce an approach that exploits domain-specificity of words as a form of domain-knowledge for entity-recognition tasks. Compared to prior work in the field, our approach is generic and completely unsupervised. We empirically show an improvement in entity extraction accuracy when features derived by our unsupervised method are used, with respect to baseline methods that do not employ domain knowledge. We also compared the results against those of existing systems that use manually crafted domain knowledge, and found them to be competitive.
Ziqi Zhang, José Iria, Fabio Ciravegna
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2010
Where LREC
Authors Ziqi Zhang, José Iria, Fabio Ciravegna
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