We develop latent Dirichlet allocation with WORDNET (LDAWN), an unsupervised probabilistic topic model that includes word sense as a hidden variable. We develop a probabilistic po...
Accurate, well-calibrated estimates of class membership probabilities are needed in many supervised learning applications, in particular when a cost-sensitive decision must be mad...
The Named Entity Recognition (NER) task has been garnering significant attention in NLP as it helps improve the performance of many natural language processing applications. In th...
In this paper, we propose a novel unsupervised approach to query segmentation, an important task in Web search. We use a generative query model to recover a query's underlyin...
The distance or similarity metric plays an important role in many natural language processing (NLP) tasks. Previous studies have demonstrated the effectiveness of a number of metr...