This paper focuses on automatically improving the readability of documents. We explore mechanisms relating to content control that could be used (i) by authors to improve the qual...
Probabilistic topic models have become popular as methods for dimensionality reduction in collections of text documents or images. These models are usually treated as generative m...
In the past, NLP has always been based on the explicit or implicit use of linguistic knowledge. In classical computer linguistic applications explicit rule based approaches prevai...
We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key a...
In this paper we present a novel approach for inducing word alignments from sentence aligned data. We use a Conditional Random Field (CRF), a discriminative model, which is estima...