Identifying the occurrences of proper names in text and the entities they refer to can be a difficult task because of the manyto-many mapping between names and their referents. We...
Background: The task of recognizing and identifying species names in biomedical literature has recently been regarded as critical for a number of applications in text and data min...
In this paper, we propose an alternative method for accessing the content of Greek historical documents printed during the 17th and 18th centuries by searching words directly in d...
Anastasios L. Kesidis, Eleni Galiotou, Basilios Ga...
An unsupervised discriminative training procedure is proposed for estimating a language model (LM) for machine translation (MT). An English-to-English synchronous context-free gra...
Zhifei Li, Ziyuan Wang, Sanjeev Khudanpur, Jason E...
Due to the lack of annotated data sets, there are few studies on machine learning based approaches to extract named entities (NEs) in clinical text. The 2009 i2b2 NLP challenge is...