Abbreviated words carry critical information in the literature of many special domains. This paper reports our research in recognizing dotted abbreviations with MaxEnt model. The k...
This paper presents a machine learning approach to the study of translationese. The goal is to train a computer system to distinguish between translated and non-translated text, in...
"Short-text clustering" is a very important research field due to the current tendency for people to use very short documents, e.g. blogs, text-messaging and others. In s...
In this paper we extend the maximum spanning tree (MST) dependency parsing framework of McDonald et al. (2005c) to incorporate higher-order feature representations and allow depen...
Mihalcea [1] discusses self-training and co-training in the context of word sense disambiguation and shows that parameter optimization on individual words was important to obtain g...