We investigate the effect of encoding additional semantic and syntactic information sources in a classification-based machine learning approach to the task of coreference resolutio...
Despite being one of the most widely-spoken languages in the world, Portuguese remains a relatively resource-poor language, for which only in recently years NLP tools such as parse...
This paper investigates the problem of automatic chemical Term Recognition (TR) and proposes to tackle the problem by fusing Symbolic and statistical techniques. Unlike other solut...
Florian Boudin, Juan Manuel Torres Moreno, Marc El...
Text classification remains one of the major fields of research in natural language processing. This paper evaluates the use of the computational tool Coh-Metrix as a means to dis...
Scott A. Crossley, Philip M. McCarthy, Danielle S....
Lattice graphs are used as underlying data structures in many statistical processing systems, including natural language processing. Lattices compactly represent multiple possible...
Christopher Collins, M. Sheelagh T. Carpendale, Ge...
The translation quality and parsing efficiency are often disappointed when Rule based Machine Translation systems deal with long sentences. Due to the complicated syntactic structu...
We present a new ensemble method that uses Entropy Guided Transformation Learning (ETL) as the base learner. The proposed approach, ETL Committee, combines the main ideas of Baggin...
"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...
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...
In this paper we describe the process of Russian and Romanian WordNet-Affect creation. WordNet-Affect is a lexical resource created on the basis of the Princeton WordNet which cont...
Victoria Bobicev, Victoria Maxim, Tatiana Prodan, ...