This paper explores the use of the homotopy method for training a semi-supervised Hidden Markov Model (HMM) used for sequence labeling. We provide a novel polynomial-time algorith...
Various types of structural information e.g., about the type of constructions in which binding constraints apply, or about the structure of names - play a central role in corefere...
Within the area of general-purpose finegrained subjectivity analysis, opinion topic identification has, to date, received little attention due to both the difficulty of the task a...
Word clustering is a conventional and important NLP task, and the literature has suggested two kinds of approaches to this problem. One is based on the distributional similarity a...
We present procedures which pool lexical information estimated from unlabeled data via the Inside-Outside algorithm, with lexical information from a treebank PCFG. The procedures ...
This paper looks at the transcribed data of patient-doctor consultations in an examination setting. The doctors are internationally qualified and enrolled in a bridging course as ...
Semantic relatedness between words is important to many NLP tasks, and numerous measures exist which use a variety of resources. Thus far, such work is confined to measuring simil...
The ability to correctly classify sentences that describe events is an important task for many natural language applications such as Question Answering (QA) and Summarisation. In ...