In this paper, we present our participation in the ImageCLEF 2005 ad-hoc track. First, we describe a preliminary pool of cross-language experiments with the ImageCLEF 2004 testbed...
In lots of natural language processing tasks, the classes to be dealt with often occur heavily imbalanced in the underlying data set and classifiers trained on such skewed data t...
Named Entity Recognition and Classification is being studied for last two decades. Since semantic features take huge amount of training time and are slow in inference, the existing...
Siddhartha Jonnalagadda, Robert Leaman, Trevor Coh...
This paper presents a maximum entropy-based named entity recognizer (NER). It differs from previous machine learning-based NERs in that it uses information from the whole document...
This paper describes a framework for defining domain specific Feature Functions in a user friendly form to be used in a Maximum Entropy Markov Model (MEMM) for the Named Entity Re...