We propose a new approach to language modeling which utilizes discriminative learning methods. Our approach is an iterative one: starting with an initial language model, in each i...
Active learning is well-suited to many problems in natural language processing, where unlabeled data may be abundant but annotation is slow and expensive. This paper aims to shed ...
We present a generative model for unsupervised coreference resolution that views coreference as an EM clustering process. For comparison purposes, we revisit Haghighi and Klein...
We improve the quality of paraphrases extracted from parallel corpora by requiring that phrases and their paraphrases be the same syntactic type. This is achieved by parsing the E...
In this paper we describe research on summarizing conversations in the meetings and emails domains. We introduce a conversation summarization system that works in multiple domains...