We propose a high-performance cascaded hybrid model for Chinese NER. Firstly, we use Boosting, a standard and theoretically wellfounded machine learning method to combine a set of...
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...
Chinese NE (Named Entity) recognition is a difficult problem because of the uncertainty in word segmentation and flexibility in language structure. This paper proposes the use of ...
This paper presents a Chinese word segmentation system that uses improved sourcechannel models of Chinese sentence generation. Chinese words are defined as one of the following fo...
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 ...