© 2014 Association for Computational Linguistics. We describe a new dependency parser
for English tweets, TWEEBOPARSER. The parser builds on several contributions: new …

Abstract The Conference on Computational Natural Language Learning features a shared
task, in which participants train and test their learning systems on the same data sets. In …

Automatic classification of sentiment is important for numerous applications such as opinion
mining, opinion summarization, contextual advertising, and market analysis. Typically …

Many NLP tools for English and German are based on manually annotated articles from the
Wall Street Journal and Frankfurter Rundschau. The average readers of these two …

Emotional distress is a common reason for seeking psychotherapy, and sharing emotional
material is central to the process of psychotherapy. However, systematic research examining …

Background The increasing availability of Electronic Health Record (EHR) data and
specifically free-text patient notes presents opportunities for phenotype extraction. Text …

We present a new algorithm for domain adaptation improving upon a discrepancy
minimization algorithm,(DM), previously shown to outperform a number of algorithms for this …

During the past decades, due to the lack of sufficient labeled data, most studies on cross-
domain parsing focus on unsupervised domain adaptation, assuming there is no target …

We study multiple-source domain adaptation, when the learner has access to abundant
labeled data from multiple-source domains and limited labeled data from the target domain …

Building clinical natural language processing (NLP) systems that work on widely varying
data is an absolute necessity because of the expense of obtaining new training data. While …