In this paper, we present classifiers ensemble approaches for biomedical named entity recognition. Generalized Winnow, Conditional Random Fields, Support Vector Machine, and Maxim...
Background: Automated information extraction from biomedical literature is important because a vast amount of biomedical literature has been published. Recognition of the biomedic...
Biomedical named entity recognition (NER) is a difficult problem in biomedical information processing due to the widespread ambiguity of terms out of context and extensive lexical ...
Seonho Kim, Juntae Yoon, Kyung-Mi Park, Hae-Chang ...
In this paper, we propose classifier ensemble selection for Named Entity Recognition (NER) as a single objective optimization problem. Thereafter, we develop a method based on gen...
Chemical named entities represent an important facet of biomedical text. We have developed a system to use character-based ngrams, Maximum Entropy Markov Models and rescoring to r...