Difference between revisions of "Bikel et al MLJ 1999"
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In this [[Category::paper]] the authors present IdentiFinder, an [[UsesMethod::HMM|Hidden Markov Model]] approach to the [[AddressesProblem::Named Entity Recognition]] problem. | In this [[Category::paper]] the authors present IdentiFinder, an [[UsesMethod::HMM|Hidden Markov Model]] approach to the [[AddressesProblem::Named Entity Recognition]] problem. | ||
| + | |||
| + | == Results == | ||
| + | * 100k words of training = 90% performance | ||
Revision as of 16:39, 19 September 2011
Citation
D. M. Bikel, R. L. Schwartz, and R. M. Weischedel. An algorithm that learns what's in a name. Machine Learning Journal, 34: 211-231, 1999.
Summary
In this paper the authors present IdentiFinder, an Hidden Markov Model approach to the Named Entity Recognition problem.
Results
- 100k words of training = 90% performance
