Speaker
Affilliation
Yahoo! Research, Barcelona
Abstract
Is natural language technology adequate for applications, e.g., in Web technology? Notwithstanding periodic surges in expectations, there is still no clear evidence supporting such claims. On the other hand, it is easy to verify that even the best NLP tools make many mistakes when deployed on real-world tasks. Domain adaptation deals with the problem of adapting existing systems (parsers, taggers, etc.) to new domains in the absence of (manually) annotated data in the new domain. Research in this area might be crucial to help NLP improve robustness and quality. In this stalk I will first present an overview of recent findings in domain adaptation. Then I will discuss our own ongoing research, mainly in the task of named entity recognition, involving both machine learning and knowledge based approaches.