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» The ConceptMapper Approach to Named Entity Recognition
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EMNLP
2007
15 years 1 months ago
Semi-Supervised Structured Output Learning Based on a Hybrid Generative and Discriminative Approach
This paper proposes a framework for semi-supervised structured output learning (SOL), specifically for sequence labeling, based on a hybrid generative and discriminative approach...
Jun Suzuki, Akinori Fujino, Hideki Isozaki
ICML
2008
IEEE
16 years 16 days ago
Boosting with incomplete information
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we pres...
Feng Jiao, Gholamreza Haffari, Greg Mori, Shaojun ...
BMCBI
2008
153views more  BMCBI 2008»
14 years 12 months ago
How to make the most of NE dictionaries in statistical NER
Background: When term ambiguity and variability are very high, dictionary-based Named Entity Recognition (NER) is not an ideal solution even though large-scale terminological reso...
Yutaka Sasaki, Yoshimasa Tsuruoka, John McNaught, ...
EMNLP
2010
14 years 9 months ago
The Necessity of Combining Adaptation Methods
Problems stemming from domain adaptation continue to plague the statistical natural language processing community. There has been continuing work trying to find general purpose al...
Ming-Wei Chang, Michael Connor, Dan Roth
83
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ACL
2006
15 years 1 months ago
Training Conditional Random Fields with Multivariate Evaluation Measures
This paper proposes a framework for training Conditional Random Fields (CRFs) to optimize multivariate evaluation measures, including non-linear measures such as F-score. Our prop...
Jun Suzuki, Erik McDermott, Hideki Isozaki